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Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 [[electronic resource] ] : 22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part IV / / edited by Dinggang Shen, Tianming Liu, Terry M. Peters, Lawrence H. Staib, Caroline Essert, Sean Zhou, Pew-Thian Yap, Ali Khan
| Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 [[electronic resource] ] : 22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part IV / / edited by Dinggang Shen, Tianming Liu, Terry M. Peters, Lawrence H. Staib, Caroline Essert, Sean Zhou, Pew-Thian Yap, Ali Khan |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XXXVIII, 809 p.) |
| Disciplina | 616.07540285 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Pattern recognition Artificial intelligence Health informatics Image Processing and Computer Vision Pattern Recognition Artificial Intelligence Health Informatics |
| ISBN | 3-030-32251-3 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Shape -- A CNN-Based Framework for Statistical Assessment of Spinal Shape and Curvature in Whole-Body MRI Images of Large Populations -- Exploiting Reliability-guided Aggregation for the Assessment of Curvilinear Structure Tortuosity -- A Surface-theoretic Approach for Statistical Shape Modeling -- Shape Instantiation from A Single 2D Image to 3D Point Cloud with One-stage Learning -- Placental Flattening via Volumetric Parameterization with Dirichlet Energy Regularization -- Fast Polynomial Approximation to Heat Diffusion in Manifolds -- Hierarchical Multi-Geodesic Model for Longitudinal Analysis of Temporal Trajectories of Anatomical Shape and Covariates -- Clustering of longitudinal shape data sets using mixture of separate or branching trajectories -- Group-wise Graph Matching of Cortical Gyral Hinges -- Multi-view Graph Matching of Cortical Landmarks -- Patient-specific Conditional Joint Models of Shape, Image Features and Clinical Indicators -- Surface-Based Spatial Pyramid Matching of Cortical Regions for Analysis of Cognitive Performance -- Prediction -- Diagnosis-guided multi-modal feature selection for prognosis prediction of lung squamous cell carcinoma -- Graph convolution based attention model for personalized disease prediction -- Predicting Early Stages of Neurodegenerative Diseases via Multi-task Low-rank Feature Learning -- Improved Prediction of Cognitive Outcomes via Globally Aligned Imaging Biomarker Enrichments Over Progressions -- Deep Granular Feature-Label Distribution Learning for Neuroimaging-based Infant Age Prediction -- End-to-End Dementia Status Prediction from Brain MRI using Multi-Task Weakly-Supervised Attention Network -- Unified Modeling of Imputation, Forecasting, and Prediction for AD Progression -- LSTM Network for Prediction of Hemorrhagic Transformation in Acute Stroke -- Inter-modality Dependence Induced Data Recovery for MCI Conversion Prediction -- Preprocessing, Prediction and Significance: Framework and Application to Brain Imaging -- Early Prediction of Alzheimer's Disease progression using Variational Autoencoder -- Integrating Heterogeneous Brain Networks for Predicting Brain Disease Conditions -- Detection and Localization -- Uncertainty-informed detection of epileptogenic brain malformations using Bayesian neural networks -- Automated Lesion Detection by Regressing Intensity-Based Distance with a Neural Network -- Intracranial aneurysms detection in 3D cerebrovascular mesh model with ensemble deep learning -- Automated Noninvasive Seizure Detection and Localization Using Switching Markov Models and Convolutional Neural Networks -- Multiple Landmarks Detection using Multi-Agent Reinforcement Learning -- Spatiotemporal Breast Mass Detection Network (MD-Net) in 4D DCE-MRI Images -- Automated Pulmonary Embolism Detection from CTPA Images using an End-to-End Convolutional Neural Network -- Pixel-wise anomaly ratings using Variational Auto-Encoders -- HR-CAM: Precise Localization of pathology using multi-level learning in CNNs -- Novel Iterative Attention Focusing Strategy for Joint Pathology Localization and Diagnosis of MCI Progression -- Automatic Vertebrae Recognition from Arbitrary Spine MRI images by a Hierarchical Self-calibration Detection Framework -- Machine Learning -- Image data validation for medical systems -- Captioning Ultrasound Images Automatically -- Feature Transformers: Privacy Preserving Life Learning Framework for Healthcare Applications -- As easy as 1, 2... 4? Uncertainty in counting tasks for medical imaging -- Generalizable Feature Learning in the Presence of Data Bias and Domain Class Imbalance with Application to Skin Lesion Classification -- Learning task-specific and shared representations in medical imaging -- Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis -- Efficient Ultrasound Image Analysis Models with Sonographer Gaze Assisted Distillation -- Fetal Pose Estimation in Volumetric MRI using 3D Convolution Neural Network -- Multi-Stage Prediction Networks for Data Harmonization -- Self-supervised Feature Learning for 3D Medical Images by Playing a Rubik's Cube -- Bayesian Volumetric Autoregressive generative models for better semisupervised learning with scarce Medical imaging data -- Data Augmentation for Regression Neural Networks -- A Dirty Multi-task Learning Method for Multi-modal Brain Imaging Genetics -- Robust and Discriminative Brain Genome Association Analysis -- Symmetric Dual Adversarial Connectomic Domain Alignment for Predicting Isomorphic Brain Graph From a Baseline Graph -- Harmonization of Infant Cortical Thickness using Surface-to-Surface Cycle-Consistent Adversarial Networks -- Quantifying Confounding Bias in Neuroimaging Datasets with Causal Inference -- Computer-aided Diagnosis -- Multi Scale Curriculum CNN for Context-Aware Breast MRI Malignancy Classification -- Deep Angular Embedding and Feature Correlation Attention for Breast MRI Cancer Analysis -- Fully Deep Learning for Slit-lamp Photo based Nuclear Cataract Grading -- Overcoming Data Limitation in Medical Visual Question Answering -- Multi-Instance Multi-Scale CNN for Medical Image Classification -- Improving Uncertainty Estimation in Convolutional Neural Networks Using Inter-rater Agreement -- Improving Skin Condition Classification with a Visual Symptom Checker Trained using Reinforcement Learning -- DScGANS: Integrate Domain Knowledge in Training Dual-Path Semi-Supervised Conditional Generative Adversarial Networks and S3VM for Ultrasonography Thyroid Nodules Classification -- Similarity steered generative adversarial network and adaptive transfer learning for malignancy characterization of hepatocellualr carcinoma -- Unsupervised Clustering of Quantitative Imaging Subtypes using Autoencoder and Gaussian Mixture Model -- Adaptive Sparsity Regularization Based Collaborative Clustering for Cancer Prognosis -- Coronary Artery Plaque Characterization from CCTA Scans using Deep Learning and Radiomics -- Response Estimation through Spatially Oriented Neural Network and Texture Ensemble (RESONATE) -- STructural Rectal Atlas Deformation (StRAD) features for characterizing intra- and peri-wall chemoradiation response on MRI -- Dynamic Routing Capsule Networks for Mild Cognitive Impairment Diagnosis -- Deep Multi-modal Latent Representation Learning for Automated Dementia Diagnosis -- Dynamic Spectral Convolution Networks with Assistant Task Training for Early MCI diagnosis -- Bridging Imaging, Genetics, and Diagnosis in a Coupled Low-Dimensional Framework -- Global and Local Interpretability for Cardiac MRI Classification -- Let's agree to disagree: learning highly debatable multirater labelling -- Coidentifciation of group-level hole structures in brain networks via Hodge Laplacian -- Confident Head Circumference Measurement from Ultrasound with Real-time Feedback for Sonographers -- Image Reconstruction and Synthesis -- Detection and Correction of Cardiac MRI Motion Artefacts during Reconstruction from k-space -- Exploiting motion for deep learning reconstruction of extremely-undersampled dynamic MRI -- VS-Net: Variable spitting network for accelerated parallel MRI reconstruction -- A Novel Loss Function Incorporating Imaging Acquisition Physics for PET Attenuation Map Generation using Deep Learning -- A Prior Learning Network for Joint Image and Sensitivity Estimation in Parallel MR Imaging -- Consensus Neural Network for Medical Image Denoising with Only Noisy Training Samples -- Consistent Brain Ageing Synthesis -- Hybrid Generative Adversarial Networks for Deep MR to CT Synthesis using Unpaired Data -- Arterial Spin Labeling Images Synthesis via Locally-constrained WGAN-GP Ensemble -- SkrGAN: Sketching-rendering Unconditional Generative Adversarial Networks for Medical Image Synthesis -- Wavelet-Based Semi-Supervised Adversarial Learning for Synthesizing Realistic 7T from 3T MRI -- DiamondGAN: Unified Multi-Modal Generative Adversarial Networks for MRI Sequences Synthesis. |
| Record Nr. | UNISA-996466178403316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 [[electronic resource] ] : 22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part I / / edited by Dinggang Shen, Tianming Liu, Terry M. Peters, Lawrence H. Staib, Caroline Essert, Sean Zhou, Pew-Thian Yap, Ali Khan
| Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 [[electronic resource] ] : 22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part I / / edited by Dinggang Shen, Tianming Liu, Terry M. Peters, Lawrence H. Staib, Caroline Essert, Sean Zhou, Pew-Thian Yap, Ali Khan |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XXXVII, 819 p. 345 illus., 294 illus. in color.) |
| Disciplina | 616.07540285 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Pattern recognition Artificial intelligence Health informatics Image Processing and Computer Vision Pattern Recognition Artificial Intelligence Health Informatics |
| ISBN | 3-030-32239-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Optical Imaging -- Enhancing OCT Signal by Fusion of GANs: Improving Statistical Power of Glaucoma Trials -- A Deep Reinforcement Learning Framework for Frame-by-frame Plaque Tracking on Intravascular Optical Coherence Tomography Image -- Multi-Index Optic Disc Quantification via MultiTask Ensemble Learning -- Retinal Abnormalities Recognition Using Regional Multitask Learning -- Unifying Structure Analysis and Surrogate-driven Function Regression for Glaucoma OCT Image Screening -- Evaluation of Retinal Image Quality Assessment Networks in Different Color-spaces -- 3D Surface-Based Geometric and Topological Quantification of Retinal Microvasculature in OCT-Angiography via Reeb Analysis -- Limited-Angle Diffuse Optical Tomography Image Reconstruction using Deep Learning -- Data-driven Enhancement of Blurry Retinal Images via Generative Adversarial Networks -- Dual Encoding U-Net for Retinal Vessel Segmentation -- A Deep Learning Design for improving Topology Coherence in Blood Vessel Segmentation -- Boundary and Entropy-driven Adversarial Learning for Fundus Image Segmentation -- Unsupervised Ensemble Strategy for Retinal Vessel Segmentation -- Fully convolutional boundary regression for retina OCT segmentation -- PM-NET: Pyramid Multi-Label Network for Optic Disc and Cup Segmentation -- Biological Age Estimated from Retinal Imaging: A Novel Biomarker of Aging -- Task Adaptive Metric Space for Medium-Shot Medical Image Classification -- Two-Stream CNN with Loose Pair Training for Multi-modal AMD Categorization -- Deep Multi Label Classification in Affine Subspaces -- Multi-scale Microaneurysms Segmentation Using Embedding Triplet Loss -- A Divide-and-Conquer Approach towards Understanding Deep Networks -- Multiclass segmentation as multitask learning for drusen segmentation in retinal optical coherence tomography -- Active Appearance Model Induced Generative Adversarial Networks for Controlled Data Augmentation -- Biomarker Localization by Combining CNN Classifier and Generative Adversarial Network -- Probabilistic Atlases to Enforce Topological Constraints -- Synapse-Aware Skeleton Generation for Neural Circuits -- Seeing Under the Cover: A Physics Guided Learning Approach for In-Bed Pose Estimation -- EDA-Net: Dense Aggregation of Deep and Shallow Information Achieves Quantitative Photoacoustic Blood Oxygenation Imaging Deep in Human Breast -- Fused Detection of Retinal Biomarkers in OCT Volumes -- Vessel-Net: Retinal Vessel Segmentation under Multi-path Supervision -- Ki-GAN: Knowledge Infusion Generative Adversarial Network for Photoacoustic Image Reconstruction in vivo -- Uncertainty guided semisupervised segmentation of retinal layers in OCT images -- Endoscopy -- Triple ANet: Adaptive Abnormal-aware Attention Network for WCE Image Classification -- Selective Feature Aggregation Network with Area-boundary Constraints for Polyp Segmentation -- Deep Sequential Mosaicking of Fetoscopic Videos -- Landmark-guided Deformable Image Registration for Supervised Autonomous Robotic Tumor Resection -- Multi-View Learning with Feature Level Fusion for Cervical Dysplasia Diagnosis -- Real-time Surface Deformation Recovery from Stereo Videos -- Microscopy -- Rectified Cross-Entropy and Upper Transition Loss for Weakly Supervised Whole Slide Image Classifier -- From Whole Slide Imaging to Microscopy: Deep Microscopy Adaptation Network for Histopathology Cancer Image Classification -- Multi-scale Cell Instance Segmentation with Keypoint Graph based Bounding Boxes -- Improving Nuclei/Gland Instance Segmentation in Histopathology Images by Full Resolution Neural Network and Spatial Constrained Loss -- Synthetic Augmentation and Feature-based Filtering for Improved Cervical Histopathology Image Classification -- Cell Tracking with Deep Learning for Cell Detection and Motion Estimation in Low-Frame-Rate -- Accelerated ML-assisted Tumor Detection in High-Resolution Histopathology Images -- Pre-operative Overall Survival Time Prediction for Glioblastoma Patients Using Deep Learning on Both Imaging Phenotype and Genotype -- Pathology-aware deep network visualization and its application in glaucoma image synthesis -- CORAL8: Concurrent Object Regression for Area Localization in Medical Image Panels -- ET-Net: A Generic Edge-Attention Guidance Network for Medical Image Segmentation -- Instance Segmentation of Biomedical Images with an Object-aware Embedding Learned with Local Constraints -- Diverse Multiple Prediction on Neural Image Reconstruction -- Deep Segmentation-Emendation Model for Gland Instance Segmentation -- Fast and Accurate Electron Microscopy Image Registration with 3D Convolution -- PlacentaNet: Automatic Morphological Characterization of Placenta Photos with Deep Learning -- Deep Multi-Instance Learning for survival prediction from Whole Slide Images -- High-Resolution Diabetic Retinopathy Image Synthesis Manipulated by Grading and Lesions -- Deep Instance-Level Hard Negative Mining Model for Histopathology Images -- Synthetic patches, real images: screening for centrosome aberrations in EM images of human cancer cells -- Patch Transformer for Multi-tagging Whole Slide Histopathology Images -- Pancreatic Cancer Detection in Whole Slide Images Using Noisy Label Annotations -- Encoding histopathological WSIs using GNN for scalable diagnostically relevant regions retrieval -- Local and Global Consistency Regularized Mean Teacher for Semi-supervised Nuclei Classification -- Perceptual Embedding Consistency for Seamless Reconstruction of Tilewise Style Transfer -- Precise Separation of Adjacent Nuclei using a Siamese Neural Network -- PFA-ScanNet: Pyramidal Feature Aggregation with Synergistic Learning for Breast Cancer Metastasis Analysis -- DeepACE: Automated Chromosome Enumeration in Metaphase Cell Images Using Deep Convolutional Neural Networks -- Unsupervised Subtyping of Cholangiocarcinoma Using A Deep Clustering Convolutional Autoencoder -- Evidence Localization for Pathology Images using Weakly Supervised Learning -- Nuclear Instance Segmentation using a Proposal-Free Spatially Aware Deep Learning Framework -- GAN-Based Image Enrichment in Digital Pathology Boosts Segmentation Accuracy -- IRNet: Instance Relation Network for Overlapping Cervical Cell Segmentation -- Weakly Supervised Cell Segmentation in Dense by Propagating from Detection Map -- Understanding Fixation in Fluorescence Microscopy via Robust Non-negative Tensor Factorization, Atlas-based Motion Correction and Functional Statistics -- ConCORDe-Net: Cell Count Regularized Convolutional Neural Network for Cell Detection, and Cell Classification in Multiplex Immunohistochemistry Images -- Multi-task learning of a deep K-nearest neighbour network for histopathological image classification and retrieval -- Multiclass deep active learning for detecting red blood cell subtypes in brightfield microscopy images -- Enhanced Cycle-Consistent Generative Adversarial Network for Color Normalization of H&E Stained Images -- Nuclei Segmentation in Histopathological Images using Two-Stage Learning -- ACE-Net: Biomedical Image Segmentation with Augmented Contracting and Expansive Paths -- CS-Net: Channel and Spatial Attention Network for Curvilinear Structure Segmentation -- PseudoEdgeNet: Nuclei Segmentation only with Point Annotations -- Adversarial Domain Adaptation and Pseudo-Labeling for Cross-Modality Microscopy Image Quantification -- Progressive Learning for Neuronal Population Reconstruction from Optical Microscopy Images -- Whole-Sample Mapping of Cancerous and Benign Tissue Properties -- Multi-Task Neural Networks with Spatial Activation for Retinal Vessel Segmentation and Artery/Vein Classification -- Fine-Scale Vessel Extraction in Fundus Images by Registration with Fluorescein Angiography -- DME-Net: Diabetic Macular Edema Grading by Auxiliary Task Learning -- Attention Guided Network for Retinal Image Segmentation -- An unsupervised domain adaptation approach to classification of stem cell-derived cardiomyocytes. |
| Record Nr. | UNISA-996466192903316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 [[electronic resource] ] : 22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part III / / edited by Dinggang Shen, Tianming Liu, Terry M. Peters, Lawrence H. Staib, Caroline Essert, Sean Zhou, Pew-Thian Yap, Ali Khan
| Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 [[electronic resource] ] : 22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part III / / edited by Dinggang Shen, Tianming Liu, Terry M. Peters, Lawrence H. Staib, Caroline Essert, Sean Zhou, Pew-Thian Yap, Ali Khan |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XXXVIII, 888 p. 359 illus., 314 illus. in color.) |
| Disciplina | 616.07540285 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Pattern recognition Artificial intelligence Health informatics Image Processing and Computer Vision Pattern Recognition Artificial Intelligence Health Informatics |
| ISBN | 3-030-32248-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Neuroimage Reconstruction and Synthesis -- Isotropic MRI Super-Resolution Reconstruction with Multi-Scale Gradient Field Prior -- A Two-Stage Multi-Loss Super-Resolution Network For Arterial Spin Labeling Magnetic Resonance Imaging -- Model Learning: Primal Dual Networks for Fast MR imaging -- Model-based Convolutional De-Aliasing Network Learning for Parallel MR Imaging -- Joint Reconstruction of PET + Parallel-MRI in a Bayesian Coupled-Dictionary MRF Framework -- Deep Learning Based Framework for Direct Reconstruction of PET Images -- Nonuniform Variational Network: Deep Learning for Accelerated Nonuniform MR Image Reconstruction -- Reconstruction of Isotropic High-Resolution MR Image from Multiple Anisotropic Scans using Sparse Fidelity Loss and Adversarial Regularization -- Single Image Based Reconstruction of High Field-like MR Images -- Deep Neural Network for QSM Background Field Removal -- RinQ Fingerprinting: Recurrence-informed Quantile Networks for Magnetic Resonance Fingerprinting -- RCA-U-Net: Residual Channel Attention U-Net for Fast Tissue Quantification in Magnetic Resonance Fingerprinting -- GANReDL: Medical Image enhancement using a generative adversarial network with real-order derivative induced loss functions -- Generation of 3D Brain MRI Using Auto-Encoding Generative Adversarial Networks -- Semi-Supervised VAE-GAN for Out-of-Sample Detection Applied to MRI Quality Control -- Disease-Image Specific Generative Adversarial Network for Brain Disease Diagnosis with Incomplete Multi-Modal Neuroimages -- Predicting the Evolution of White Matter Hyperintensities in Brain MRI using Generative Adversarial Networks and Irregularity Map -- CoCa-GAN: Common-feature-learning-based Context-aware Generative Adversarial Network for Glioma Grading -- Degenerative Adversarial NeuroImage Nets: Generating Images that Mimic Disease Progression -- Neuroimage Segmentation -- Scribble-based Hierarchical Weakly Supervised Learning for Brain Tumor Segmentation -- 3D Dilated Multi-Fiber Network for Real-time Brain Tumor Segmentation in MRI -- Refined-Segmentation R-CNN: A Two-stage Convolutional Neural Network for Punctate White Matter Lesion Segmentation in Preterm Infants -- VoteNet: A Deep Learning Label Fusion Method for Multi-Atlas Segmentation -- Weakly Supervised Brain Lesion Segmentation via Attentional Representation Learning -- Scalable Neural Architecture Search for 3D Medical Image Segmentation -- Unified Attentional Generative Adversarial Network for Brain Tumor Segmentation From Multimodal Unpaired Images -- High Resolution Medical Image Segmentation using Data-swapping Method -- X-Net: Brain Stroke Lesion Segmentation Based on Depthwise Separable Convolution and Long-range Dependencies -- Multi-View Semi-supervised 3D Whole Brain Segmentation with a Self-Ensemble Network -- CLCI-Net: Cross-Level Fusion and Context Inference Networks for Lesion Segmentation of Chronic Stroke -- Brain Segmentation from k-space with End-to-end Recurrent Attention Network -- Spatial Warping Network for 3D Segmentation of the Hippocampus in MR Images -- CompareNet: Anatomical Segmentation Network with Deep Non-local Label Fusion -- A Joint 3D+2D Fully Convolutional Framework for Subcortical Segmentation -- U-ReSNet: Ultimate coupling of Registration and Segmentation with deep Nets -- Generative adversarial network for segmentation of motion affected neonatal brain MRI -- Interactive deep editing framework for medical image segmentation -- Multiple Sclerosis Lesion Segmentation with Tiramisu and 2.5D Stacked Slices -- Improving Multi-Atlas Segmentation by Convolutional Neural Network Based Patch Error Estimation -- Unsupervised deep learning for Bayesian brain MRI segmentation -- Online atlasing using an iterative centroid -- ARS-Net: Adaptively Rectified Supervision Network for Automated 3D Ultrasound Image Segmentation -- Complete Fetal Head Compounding from Multi-View 3D Ultrasound -- SegNAS3D: Network Architecture Search with Derivative-Free Global Optimization for 3D Image Segmentation -- Overfitting of neural nets under class imbalance: Analysis and improvements for segmentation -- RSANet: Recurrent Slice-wise Attention Network for Multiple Sclerosis Lesion Segmentation -- Deep Cascaded Attention Networks for Multi-task Brain Tumor Segmentation -- Partially Reversible U-Net for Memory-Efficient Volumetric Image Segmentation -- 3DQ: Compact Quantized Neural Networks for Volumetric Whole Brain Segmentation -- Robust Multimodal Brain Tumor Segmentation via Feature Disentanglement and Gated Fusion -- Multi-task Attention-based Semi-supervised Learning for Medical Image Segmentation -- AssemblyNet: A Novel Deep Decision-Making Process for Whole Brain MRI Segmentation -- Automated Parcellation of the Cortex using Structural Connectome Harmonics -- Hierarchical parcellation of the cerebellum -- Intrinsic Patch-based Cortical Anatomical Parcellation using Graph Convolutional Neural Network on Surface Manifold -- Cortical Surface Parcellation using Spherical Convolutional Neural Networks -- A Soft STAPLE Algorithm Combined with Anatomical Knowledge -- Diffusion Weighted Magnetic Resonance Imaging -- Multi-Stage Image Quality Assessment of Diffusion MRI via Semi-Supervised Nonlocal Residual Networks -- Reconstructing High-Quality Diffusion MRI Data from Orthogonal Slice-Undersampled Data Using Graph Convolutional Neural Networks -- Surface-based Tracking of U-fibers in the Superficial White Matter -- Probing Brain Micro-Architecture by Orientation Distribution Invariant Identification of Diffusion Compartments -- Characterizing Non-Gaussian Diffusion in Heterogeneously Oriented Tissue Microenvironments -- Topographic Filtering of Tractograms as Vector Field Flows -- Enabling Multi-Shell b-Value Generalizability of Data-Driven Diffusion Models with Deep SHORE -- Super-Resolved q-Space Deep Learning -- Joint Identification of Network Hub Nodes by Multivariate Graph Inference -- Deep white matter analysis: fast, consistent tractography segmentation across populations and dMRI acquisitions -- Improved Placental Parameter Estimation Using Data-Driven Bayesian Modelling -- Optimal experimental design for biophysical modelling in multidimensional diffusion MRI -- DeepTract: A Probabilistic Deep Learning Framework for White Matter Fiber Tractography -- Fast and Scalable Optimal Transport for Brain Tractograms -- A hybrid deep learning framework for integrated segmentation and registration: evaluation on longitudinal white matter tract changes -- Constructing Consistent Longitudinal Brain Networks by Group-wise Graph Learning -- Functional Neuroimaging (fMRI) -- Multi-layer temporal network analysis reveals increasing temporal reachability and spreadability in the first two years of life -- A matched filter decomposition of fMRI into resting and task components -- Identification of Abnormal Circuit Dynamics in Major Depressive Disorder via Multiscale Neural Modeling of Resting-state fMRI -- Integrating Functional and Structural Connectivities via Diffusion-Convolution-Bilinear Neural Network -- Invertible Network for Classification and Biomarker Selection for ASD -- Integrating Neural Networks and Dictionary Learning for Multidimensional Clinical Characterizations from Functional Connectomics Data -- Revealing Functional Connectivity by Learning Graph Laplacian -- Constructing Multi-Scale Connectome Atlas by Learning Common Topology of Brain Networks -- Autism Classification Using Topological Features and Deep Learning: A Cautionary Tale -- Identify Hierarchical Structures from Task-based fMRI Data via Hybrid Spatiotemporal Neural Architecture Search Net -- A Deep Learning Framework for Noise Component Detection from Resting-state Functional MRI -- A Novel Graph Wavelet Model for Brain Multi-Scale Functional-structural Feature Fusion -- Combining Multiple Behavioral Measures and Multiple Connectomes via Multiway Canonical Correlation Analysis -- Decoding brain functional connectivity implicated in AD and MCI -- Interpretable Feature Learning Using Multi-Output Takagi-Sugeno-Kang Fuzzy System for Multi-center ASD Diagnosis -- Interpretable Multimodality Embedding Of Cerebral Cortex Using Attention Graph Network For Identifying Bipolar Disorder -- Miscellaneous Neuroimaging -- Doubly Weak Supervision of Deep Learning Models for Head CT -- Detecting Acute Strokes from Non-Contrast CT Scan Data Using Deep Convolutional Neural Networks -- FocusNet: Imbalanced Large and Small Organ Segmentation with an End-to-End Deep Neural Network for Head and Neck CT Images -- Regression-based Line Detection Network for Delineation of Largely Deformed Brain Midline -- Siamese U-Net with Healthy Template for Accurate Segmentation of Intracranial Hemorrhage -- Automated Infarct Segmentation from Follow-up Non-Contrast CT Scans in Patients with Acute Ischemic Stroke Using Dense Multi-Path Contextual Generative Adversarial Network -- Recurrent sub-volume analysis of head CT scans for the detection of intracranial hemorrhage -- Cephalometric Landmark Detection by Attentive Feature Pyramid Fusion and Regression-Voting. |
| Record Nr. | UNISA-996466178703316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 [[electronic resource] ] : 22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part V / / edited by Dinggang Shen, Tianming Liu, Terry M. Peters, Lawrence H. Staib, Caroline Essert, Sean Zhou, Pew-Thian Yap, Ali Khan
| Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 [[electronic resource] ] : 22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part V / / edited by Dinggang Shen, Tianming Liu, Terry M. Peters, Lawrence H. Staib, Caroline Essert, Sean Zhou, Pew-Thian Yap, Ali Khan |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XXXVI, 695 p. 387 illus., 286 illus. in color.) |
| Disciplina | 616.07540285 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Pattern recognition Artificial intelligence Health informatics Image Processing and Computer Vision Pattern Recognition Artificial Intelligence Health Informatics |
| ISBN | 3-030-32254-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Computer Assisted Interventions -- Robust Cochlear Modiolar Axis Detection in CT -- Learning to Avoid Poor Images: Towards Task-aware C-arm Cone-beam CT Trajectories -- Optimizing Clearance of Bézier Spline Trajectories for Minimally-Invasive Surgery -- Direct Visual and Haptic Volume Rendering of Medical Data Sets for an Immersive Exploration in Virtual Reality -- Triplet Feature Learning on Endoscopic Video Manifold for Real-time Gastrointestinal Image Retargeting -- A Novel Endoscopic Navigation System: Simultaneous Endoscope and Radial Ultrasound Probe Tracking Without External Trackers -- An Extremely Fast and Precise Convolutional Neural Network for Recognition and Localization of Cataract Surgical Tools -- Semi-autonomous Robotic Anastomoses of Vaginal Cuffs using Marker Enhanced 3D Imaging and Path Planning -- Augmented Reality "X-Ray Vision" for Laparoscopic Surgery using Optical See-Through Head-Mounted Display -- Interactive Endoscopy: A Next-Generation, Streamlined User Interface for Lung Surgery Navigation -- Non-invasive Assessment of In Vivo Auricular Cartilage by Ultrashort Echo Time (UTE) T2* Mapping -- INN: Inflated Neural Networks for IPMN Diagnosis -- Development of an Multi-objective Optimized Planning Method for Microwave Liver Tumor Ablation -- Generating large labeled data sets for laparoscopic image processing tasks using unpaired image-to-image translation -- Mask-MCNet: Instance Segmentation in 3D Point Cloud of Intra-oral Scans -- Physics-based Deep Neural Network for Augmented Reality during Liver Surgery -- Detecting Cannabis-Associated Cognitive Impairment using Resting-state fNIRS -- Cross-Domain Conditional Generative Adversarial Networks for Stereoscopic Hyperrealism in Surgical Training -- A Free-view, 3D Gaze-Guided Robotic Scrub Nurse -- Haptic Modes for Multiparameter Control in Robotic Surgery -- Learning to Detect Collisions for Continuum Manipulators without a Prior Model -- Simulation of Balloon-Expandable Coronary Stent Apposition with Plastic Beam Elements -- Virtual Cardiac Surgical Planning through Hemodynamics Simulation and Design Optimization of Fontan Grafts -- 3D Modelling of the residual freezing for renal cryoablation simulation and prediction -- A generative model of hyperelastic strain energy density functions for real-time simulation of brain tissue deformation -- Variational Mandible Shape Completion for Virtual Surgical Planning -- Markerless Image-to-Face Registration for Untethered Augmented Reality in Head and Neck Surgery -- Towards a first mixed-reality first person point of view needle navigation system -- Concept-Centric Visual Turing Tests for Method Validation -- Transferring from ex-vivo to in-vivo: Instrument Localization in 3D Cardiac Ultrasound Using Pyramid-UNet with Hybrid Loss -- A Sparsely Distributed Intra-cardial Ultrasonic Array for Real-time Endocardial Mapping -- FetusMap: Fetal Pose Estimation in 3D Ultrasound -- Agent with Warm Start and Active Termination for Plane Localization in 3D Ultrasound -- Learning and Understanding Deep Spatio-Temporal Representations from Free-Hand Fetal Ultrasound Sweeps -- User guidance for point-of-care echocardiography using multi-task deep neural network -- Integrating 3D Geometry of Organ for Improving Medical Imaging Segmentation -- Estimating Reference Bony Shape Model for Personalized Surgical Reconstruction of Posttraumatic Facial Defects -- A New Approach of Predicting Facial Changes following Orthognathic Surgery using Realistic Lip Sliding Effect -- An Automatic Approach to Reestablish Final Dental Occlusion for 1-Piece Maxillary Orthognathic Surgery -- MIC meets CAI -- A Two-stage Framework for Real-time Guidewire Endpoint Localization -- Investigating the role of VR in a simulation-based medical planning system for coronary interventions -- Learned Full-sampling Reconstruction -- A deep regression model for seed localization in prostate brachytherapy -- Model-Based Surgical Recommendations for Optimal Placement of Epiretinal Implants -- Towards Multiple Instance Learning and Hermann Weyl's Discrepancy for Robust Image-Guided Bronchoscopic Intervention -- Learning Where to Look While Tracking Instruments in Robot-assisted Surgery -- Efficient Soft-Constrained Clustering for Group-Based Labeling -- Leveraging Other Datasets for Medical Imaging Classification: Evaluation of Transfer, Multi-task and Semi-supervised Learning -- Incorporating Temporal Prior from Motion Flow for Instrument Segmentation in Minimally Invasive Surgery Video -- Hard Frame Detection and Online Mapping for Surgical Phase Recognition -- Automated Surgical Activity Recognition with One Labeled Sequence -- Using 3D Convolutional Neural Networks to learn spatiotemporal features for automatic surgical gesture recognition in video -- Surgical Skill Assessment on In-Vivo Clinical Data via the Clearness of Operating Field -- Graph Neural Network for Interpreting Task-fMRI Biomarkers -- Achieving Accurate Segmentation of Nasopharyngeal Carcinoma in MR Images through Recurrent Attention -- Brain Dynamics Through the Lens of Statistical Mechanics by Unifying Structure and Function -- Synthesis and Inpainting-based MR-CT Registration for Image-Guided Thermal Ablation of Liver Tumors -- CFEA: Collaborative Feature Ensembling Adaptation for Domain Adaptation in Unsupervised Optic Disc and Cup Segmentation -- Gastric cancer detection from endoscopic images using synthesis by GAN -- Deep Local-Global Refinement Network for Stent Analysis in IVOCT Images -- Generalized Non-Rigid Point Set Registration with Hybrid Mixture Models Considering Anisotropic Positional Uncertainties -- Mixed-Supervision Multilevel GAN for Image Quality Enhancement -- Combined Learning for Similar Tasks with Domain-Switching Networks -- Real-time 3D reconstruction of colonoscopic surfaces for determining missing regions -- Human Pose Estimation on Privacy-Preserving Low-Resolution Depth Images -- A Mesh-Aware Ball-Pivoting Algorithm for Generating the Virtual Arachnoid Mater -- Attenuation Imaging with Pulse-Echo Ultrasound based on an Acoustic Reflector -- SWTV-ACE: Spatially Weighted Regularization based Attenuation Coefficient Estimation Method for Hepatic Steatosis Detection -- Deep Learning-based Universal Beamformer for Ultrasound Imaging -- Towards whole placenta segmentation at late gestation using multi-view ultrasound images -- Single Shot Needle Tip Localization in 2D Ultrasound -- Discriminative Correlation Filter Network for Robust Landmark Tracking in Ultrasound Guided Intervention -- Echocardiography Segmentation by Quality Translation using Anatomically Constrained CycleGAN -- Matwo-CapsNet: a Multi-Label Semantic Segmentation Capsules Network -- LumiPath - Towards Real-time Physically-based Rendering on Embedded Devices -- An Integrated Multi-Physics Finite Element Modeling Framework for Deep Brain Stimulation: Preliminary Study on Impact of Brain Shift on Neuronal Pathways. |
| Record Nr. | UNISA-996466176503316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 [[electronic resource] ] : 22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part VI / / edited by Dinggang Shen, Tianming Liu, Terry M. Peters, Lawrence H. Staib, Caroline Essert, Sean Zhou, Pew-Thian Yap, Ali Khan
| Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 [[electronic resource] ] : 22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part VI / / edited by Dinggang Shen, Tianming Liu, Terry M. Peters, Lawrence H. Staib, Caroline Essert, Sean Zhou, Pew-Thian Yap, Ali Khan |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XXXVIII, 860 p. 476 illus., 308 illus. in color.) |
| Disciplina | 616.07540285 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Pattern recognition Artificial intelligence Health informatics Image Processing and Computer Vision Pattern Recognition Artificial Intelligence Health Informatics |
| ISBN | 3-030-32226-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Computed Tomography -- Multi-Scale Coarse-to-Fine Segmentation for Screening Pancreatic Ductal Adenocarcinoma -- MVP-Net: Multi-view FPN with Position-aware Attention for Deep Universal Lesion Detection -- Spatial-Frequency Non-Local Convolutional LSTM Network for pRCC classification -- BCD-Net for Low-dose CT Reconstruction: Acceleration, Convergence, and Generalization -- Abdominal Adipose Tissue Segmentation in MRI with Double Loss Function Collaborative Learning -- Closing the Gap between Deep and Conventional Image Registration using Probabilistic Dense Displacement Networks -- Generating Pareto optimal dose distributions for radiation therapy treatment planning -- PAN: Projective Adversarial Network for Medical Image Segmentation -- Generative Mask Pyramid Network for CT/CBCT Metal Artifact Reduction with Joint Projection-Sinogram Correction -- Multi-Class Gradient Harmonized Dice Loss with Application to Knee MR Image Segmentation -- LSRC: A Long-Short Range Context-Fusing Framework for Automatic 3D Vertebra Localization -- Contextual Deep Regression Network for Volume Estimation in Orbital CT -- Multi-scale GANs for Memory-efficient Generation of High Resolution Medical Images -- Deep Learning based Metal Artifacts Reduction in post-operative Cochlear Implant CT Imaging -- ImHistNet: Learnable Image Histogram Based DNN with Application to Noninvasive Determination of Carcinoma Grades in CT Scans -- DPA-DenseBiasNet: Semi-supervised 3D Fine Renal Artery Segmentation with Dense Biased Network and Deep Priori Anatomy -- Semi-supervised Segmentation of Liver Using Adversarial Learning with Deep Atlas Prior -- Pairwise Semantic Segmentation via Conjugate Fully Convolutional Network -- Unsupervised Deformable Image Registration Using Cycle-Consistent CNN -- Volumetric Attention for 3D Medical Image Segmentation and Detection -- Improving Deep Lesion Detection Using 3D Contextual and Spatial Attention -- MULAN: Multitask Universal Lesion Analysis Network for Joint Lesion Detection, Tagging, and Segmentation -- Artifact Disentanglement Network for Unsupervised Metal Artifact Reduction -- AirwayNet: A Voxel-Connectivity Aware Approach for Accurate Airway Segmentation Using Convolutional Neural Networks -- Integrating cross-modality hallucinated MRI with CT to aid mediastinal lung tumor segmentation -- Bronchus Segmentation and Classification by Neural Networks and Linear Programming -- Unsupervised Segmentation of Micro-CT Images of Lung Cancer Specimen Using Deep Generative Models -- Normal appearance autoencoder for lung cancer detection and segmentation -- mlVIRNET: Multilevel Variational Image Registration Network -- NoduleNet: Decoupled False Positive Reduction for Pulmonary Nodule Detection and Segmentation -- Encoding CT Anatomy Knowledge for Unpaired Chest X-ray Image Decomposition -- Targeting Precision with Data Augmented Samples in Deep Learning -- Pulmonary Vessel Segmentation based on Orthogonal Fused U-Net++ of Chest CT Images -- Attentive CT Lesion Detection Using Deep Pyramid Inference with Multi-Scale Booster -- Deep Variational Networks with Exponential Weighting for Learning Computed Tomography -- R2-Net: Recurrent and Recursive Network for Sparse-view CT Artifacts Removal -- Stereo-Correlation and Noise-Distribution Aware ResVoxGAN for Dense Slices Reconstruction and Noise Reduction in Thick Low-Dose CT -- Harnessing 2D Networks and 3D Features for Automated Pancreas Segmentation from Volumetric CT Images -- Tubular Structure Segmentation Using Spatial Fully Connected Network With Radial Distance Loss for 3D Medical Images -- Bronchial Cartilage Assessment with Model-Based GAN Regressor -- Adversarial optimization for joint registration and segmentation in prostate CT radiotherapy -- Probabilistic Point Cloud Reconstructions for Vertebral Shape Analysis -- Automatically Localizing a Large Set of Spatially Correlated Key Points: A Case Study in Spine Imaging -- Permutohedral Attention Module for Efficient Non-Local Neural Networks -- Improving RetinaNet for CT Lesion Detection with Dense Masks from Weak RECIST Labels -- X-ray Imaging -- PRSNet: Part Relation and Selection Network for Bone Age Assessment -- Mask Embedding for Realistic High-resolution Medical Image Synthesis -- TUNA-Net: Task-oriented UNsupervised Adversarial Network for Disease Recognition in Cross-Domain Chest X-rays -- Misshapen Pelvis Landmark Detection by Spatial Local Correlation Mining for Diagnosing Developmental Dysplasia of the Hip -- Adversarial Policy Gradient for Deep Learning Image Augmentation -- Weakly Supervised ROI Mining Toward Universal Fracture Detection in Pelvic X-ray -- Learning from Suspected Target: Bootstrapping Performance for Breast Cancer Detection in Mammography -- From Unilateral to Bilateral Learning: Detecting Mammogram Mass with Contrasted Bilateral Network -- Signed Laplacian Deep Learning with Adversarial Augmentation for Improved Mammography Diagnosis -- Uncertainty measurements for the reliable classification of mammograms -- GraphX$^{NET}-$ Chest X-Ray Classification Under Extreme Minimal Supervision -- 3DFPN-HS2: 3D Feature Pyramid Network Based High Sensitivity and Specificity Pulmonary Nodule Detection -- Automated detection and type classification of central venous catheters in chest X-rays -- A Comprehensive Framework for Accurate Classification of Pulmonary Nodules -- Hand Pose Estimation for Pediatric Bone Age Assessment -- An Attention-Guided Deep Regression Model for Landmark Detection in Cephalograms -- Learning-based X-ray Image Denoising utilizing Model-based Image Simulations -- LVC-Net: Medical image segmentation with noisy label based on Local Visual Cues -- Unsupervised Cone-Beam Computed Tomography (CBCT) segmentation based on adversarial learning domain adaptation -- Pick-and-Learn: Automatic Quality Evaluation for Noisy-Labeled Image Segmentation -- Anatomical Priors for Image Segmentation via Post-Processing with Denoising Autoencoders -- Simultaneous Lung Field Detection and Segmentation for Pediatric ChestRadiographs -- Deep Esophageal Clinical Target Volume Delineation using Encoded 3D Spatial Context of Tumor, Lymph Nodes, and Organs At Risk -- Weakly Supervised Segmentation Framework with Uncertainty: A Study on Pneumothorax Segmentation in Chest X-ray -- Multi-task Localization and Segmentation for X-ray Guided Planning in Knee Surgery -- Towards fully automatic X-ray to CT registration -- Adaptive image-feature learning for disease classification using inductive graph networks -- How to learn from unlabeled volume data: Self-Supervised 3D Context Feature Learning -- Probabilistic Radiomics: Ambiguous Diagnosis with Controllable Shape Analysis -- Extract Bone Parts without Human Prior: End-to-end Convolutional Neural Network for Pediatric Bone Age Assessment -- Quantifying and Leveraging Classification Uncertainty for Chest Radiograph Assessment -- Adversarial regression training for visualizing the progression of chronic obstructive pulmonary disease with chest x-rays -- Medical-based Deep Curriculum Learning for Improved Fracture Classification -- Realistic Breast Mass Generation through BIRADS Category -- Learning from Longitudinal Mammography Studies -- Automated Radiology Report Generation via Multi-view Image Fusion and Medical Concept Enrichment -- Multi-label Thoracic Disease Image Classification with Cross-attention Networks -- InfoMask: Masked Variational Latent Representation to Localize Chest Disease -- Longitudinal Change Detection on Chest X-rays using Geometric Correlation Maps -- Adversarial Pulmonary Pathology Translation for Pairwise Chest X-ray Data Augmentation -- Semi-Supervised Learning by Disentangling and Self-Ensembling over Stochastic Latent Space -- An Automated Cobb Angle Estimation Method Using Convolutional Neural Network with Area Limitation -- Endotracheal Tube Detection and Segmentation in Chest Radiographs using Synthetic Data -- Learning Interpretable Features via Adversarially Robust Optimization -- Synthesize Mammogram from Digital Breast Tomosynthesis with Gradient Guided cGANs -- Semi-supervised Medical Image Segmentation via Learning Consistency under Transformations -- Improved Inference via Deep Input Transfer -- Neural Architecture Search for Adversarial Medical Image Segmentation -- MeshSNet: Deep Multi-Scale Mesh Feature Learning for End-to-End Tooth Labeling on 3D Dental Surfaces -- Improving Robustness of Medical Image Diagnosis with Denoising Convolutional Neural Networks. |
| Record Nr. | UNISA-996466193603316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 [[electronic resource] ] : 22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part II / / edited by Dinggang Shen, Tianming Liu, Terry M. Peters, Lawrence H. Staib, Caroline Essert, Sean Zhou, Pew-Thian Yap, Ali Khan
| Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 [[electronic resource] ] : 22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part II / / edited by Dinggang Shen, Tianming Liu, Terry M. Peters, Lawrence H. Staib, Caroline Essert, Sean Zhou, Pew-Thian Yap, Ali Khan |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XXXVIII, 874 p.) |
| Disciplina |
006.6
006.37 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Pattern recognition Artificial intelligence Health informatics Image Processing and Computer Vision Pattern Recognition Artificial Intelligence Health Informatics |
| ISBN | 3-030-32245-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Image Segmentation -- Searching Learning Strategy with Reinforcement Learning for 3D Medical Image Segmentation -- Comparative Evaluation of Hand-Engineered and Deep-Learned Features for Neonatal Hip Bone Segmentation in Ultrasound -- Unsupervised Quality Control of Image Segmentation based on Bayesian Learning -- One Network To Segment Them All: A General, Lightweight System for Accurate 3D Medical Image Segmentation -- 'Project & Excite' Modules for Segmentation of Volumetric Medical Scans -- Assessing Reliability and Challenges of Uncertainty Estimations for Medical Image Segmentation -- Learning Cross-Modal Deep Representations for Multi-Modal MR Image Segmentation -- Extreme Points Derived Confidence Map as a Cue For Class-Agnostic Segmentation Using Deep Neural Network -- Hetero-Modal Variational Encoder-Decoder for Joint Modality Completion and Segmentation -- Instance Segmentation from Volumetric Biomedical Images without Voxel-Wise Labeling -- Optimizing the Dice Score and Jaccard Index for Medical Image Segmentation: Theory & Practice -- Dual Adaptive Pyramid Network for Cross-Stain Histopathology Image Segmentation -- HD-Net: Hybrid Discriminative Network for Prostate Segmentation in MR Images -- PHiSeg: Capturing Uncertainty in Medical Image Segmentation -- Neural Style Transfer Improves 3D Cardiovascular MR Image Segmentation on Inconsistent Data -- Supervised Uncertainty Quantification for Segmentation with Multiple Annotations -- 3D Tiled Convolution for Effective Segmentation of Volumetric Medical Images -- Hyper-Pairing Network for Multi-Phase Pancreatic Ductal Adenocarcinoma Segmentation -- Statistical intensity- and shape-modeling to automate cerebrovascular segmentation from TOF-MRA data -- Segmentation of Vessels in Ultra High Frequency Ultrasound Sequences using Contextual Memory -- Accurate Esophageal Gross Tumor Volume Segmentation in PET/CT using Two-Stream Chained 3D Deep Network Fusion -- Mixed-Supervised Dual-Network for Medical Image Segmentation -- Fully Automated Pancreas Segmentation with Two-stage 3D Convolutional Neural Networks -- Globally Guided Progressive Fusion Network for 3D Pancreas Segmentation -- Automatic Segmentation of Muscle Tissue and Inter-muscular Fat in Thigh and Calf MRI Images -- Resource Optimized Neural Architecture Search for 3D Medical Image Segmentation -- Radiomics-guided GAN for Segmentation of Liver Tumor without Contrast Agents -- Liver Segmentation in Magnetic Resonance Imaging via Mean Shape Fitting with Fully Convolutional Neural Networks -- Unsupervised Domain Adaptation via Disentangled Representations: Application to Cross-Modality Liver Segmentation -- Automatic Segmentation of Vestibular Schwannoma from T2-Weighted MRI by Deep Spatial Attention with Hardness-Weighted Loss -- Learning Shape Representation on Sparse Point Clouds for Volumetric Image Segmentation -- Collaborative Multi-agent Learning for MR Knee Articular Cartilage Segmentation -- 3D U2-Net: A 3D Universal U-Net for Multi-Domain Medical Image Segmentation -- Impact of Adversarial Examples on Deep Learning Segmentation Models -- Multi-Resolution Path CNN with Deep Supervision for Intervertebral Disc Localization and Segmentation -- Automatic paraspinal muscle segmentation in patients with lumbar pathology using deep convolutional neural network -- Constrained Domain Adaptation for Segmentation -- Image Registration -- Image-and-Spatial Transformer Networks for Structure-Guided Image Registration -- Probabilistic Multilayer Regularization Network for Unsupervised 3D Brain Image Registration -- A deep learning approach to MR-less spatial normalization for tau PET images -- TopAwaRe: Topology-Aware Registration -- Multimodal Data Registration for Brain Structural Association Networks -- Dual-Stream Pyramid Registration Network -- A Cooperative Autoencoder for Population-Based Regularization of CNN Image Registration -- Conditional Segmentation in Lieu of Image Registration -- On the applicability of registration uncertainty -- DeepAtlas: Joint Semi-Supervised Learning of Image Registration and Segmentation -- Linear Time Invariant Model based Motion Correction (LiMo-Moco) of Dynamic Radial Contrast Enhanced MRI -- Incompressible image registration using divergence-conforming B-splines -- Cardiovascular Imaging -- Direct Quantification for Coronary Artery Stenosis Using Multiview Learning -- Bayesian Optimization on Large Graphs via a Graph Convolutional Generative Model: Application in Cardiac Model Personalization -- Discriminative Coronary Artery Tracking via 3D CNN in Cardiac CT Angiography -- Multi-modality Whole-Heart and Great Vessel Segmentation in Congenital Heart Disease using Deep Neural Networks and Graph Matching -- Harmonic Balance Techniques in Cardiovascular Fluid Mechanics -- Deep learning within a priori temporal feature spaces for large-scale dynamic MR image reconstruction: Application to 5-D cardiac MR Multitasking -- k-t NEXT: Dynamic MR Image Reconstruction Exploiting Spatio-temporal Correlations -- Model-based reconstruction for highly accelerated first-pass perfusion cardiac MRI -- Learning Shape Priors for Robust Cardiac MR Segmentation from Multi-view images -- Right Ventricle Segmentation in Short-Axis MRI Using A Shape Constrained Dense Connected U-net -- Self-Supervised Learning for Cardiac MR Image Segmentation by Anatomical Position Prediction -- A Fine-Grain Error Map Prediction and Segmentation Quality Assessment Framework for Whole-Heart Segmentation -- Cardiac Segmentation from LGE MRI Using Deep Neural Network Incorporating Shape and Spatial Priors -- Curriculum semi-supervised segmentation -- A Multi-modal Network for Cardiomyopathy Death Risk Prediction with CMR Images and Clinical Information -- 3D Cardiac Shape Prediction with Deep Neural Networks: Simultaneous Use of Images and Patient Metadata -- Discriminative Consistent Domain Generation for Semi-supervised Learning -- Uncertainty-aware Self-ensembling Model for Semi-supervised 3D Left Atrium Segmentation -- MSU-Net: Multiscale Statistical U-Net for Real-time 3D Cardiac MRI Video Segmentation -- The Domain Shift Problem of Medical Image Segmentation and Vendor-Adaptation by Unet-GAN -- Cardiac MRI Segmentation with Strong Anatomical Guarantees -- Decompose-and-Integrate Learning for Multi-class Segmentation in Medical Images -- Missing Slice Imputation in Population CMR Imaging via Conditional Generative Adversarial Nets -- Unsupervised Standard Plane Synthesis in Population Cine MRI via Cycle-Consistent Adversarial Networks -- Data Efficient Unsupervised Domain Adaptation for Cross-Modality Image Segmentation -- Recurrent Aggregation Learning for Multi-View Echocardiographic Sequences Segmentation -- Echocardiography View Classification Using Quality Transfer Star Generative Adversarial Networks -- Dual-view Joint Estimation of Left Ventricular Ejection Fraction with Uncertainty Modelling in Echocardiograms -- Frame Rate Up-Conversion in Echocardiography Using a Conditioned Variational Autoencoder and Generative Adversarial Model -- Annotation-Free Cardiac Vessel Segmentation via Knowledge Transfer from Retinal Images -- DeepAAA: clinically applicable and generalizable detection of abdominal aortic aneurysm using deep learning -- Texture-based classification of significant stenosis in CCTA multi-view images of coronary arteries -- Fourier Spectral Dynamic Data Assimilation: Interlacing CFD with 4D flow MRI -- Quality Control-Driven Image Segmentation Towards Reliable Automatic Image Analysis in Large-Scale Cardiovascular Magnetic Resonance Aortic Cine Imaging -- HFA-Net: 3D Cardiovascular Image Segmentation with Asymmetrical Pooling and Content-Aware Fusion -- Spectral CT based training dataset generation and augmentation for conventional CT vascular segmentation -- Context-Aware Inductive Bias Learning for Vessel Border Detection in Multi-modal Intracoronary Imaging -- Growth, Development, Atrophy and Progression -- Neural parameters estimation for brain tumor growth modeling -- Learning-Guided Infinite Network Atlas Selection for Predicting Longitudinal Brain Network Evolution from a Single Observation -- Deep Probabilistic Modeling of Glioma Growth -- Surface-Volume Consistent Construction of Longitudinal Atlases for the Early Developing Brains -- Variational Autoencoder for Regression: Application to Brain Aging Analysis -- Early Development of Infant Brain Complex Network -- Revealing Developmental Regionalization of Infant Cerebral Cortex Based on Multiple Cortical Properties -- Continually Modeling Alzheimer's Disease Progression via Deep Multi-Order Preserving Weight Consolidation -- Disease Knowledge Transfer across Neurodegenerative Diseases. |
| Record Nr. | UNISA-996466191303316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 : 22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part III / / edited by Dinggang Shen, Tianming Liu, Terry M. Peters, Lawrence H. Staib, Caroline Essert, Sean Zhou, Pew-Thian Yap, Ali Khan
| Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 : 22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part III / / edited by Dinggang Shen, Tianming Liu, Terry M. Peters, Lawrence H. Staib, Caroline Essert, Sean Zhou, Pew-Thian Yap, Ali Khan |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XXXVIII, 888 p. 359 illus., 314 illus. in color.) |
| Disciplina |
616.07540285
616.0757 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Pattern recognition Artificial intelligence Health informatics Image Processing and Computer Vision Pattern Recognition Artificial Intelligence Health Informatics |
| ISBN | 3-030-32248-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Neuroimage Reconstruction and Synthesis -- Isotropic MRI Super-Resolution Reconstruction with Multi-Scale Gradient Field Prior -- A Two-Stage Multi-Loss Super-Resolution Network For Arterial Spin Labeling Magnetic Resonance Imaging -- Model Learning: Primal Dual Networks for Fast MR imaging -- Model-based Convolutional De-Aliasing Network Learning for Parallel MR Imaging -- Joint Reconstruction of PET + Parallel-MRI in a Bayesian Coupled-Dictionary MRF Framework -- Deep Learning Based Framework for Direct Reconstruction of PET Images -- Nonuniform Variational Network: Deep Learning for Accelerated Nonuniform MR Image Reconstruction -- Reconstruction of Isotropic High-Resolution MR Image from Multiple Anisotropic Scans using Sparse Fidelity Loss and Adversarial Regularization -- Single Image Based Reconstruction of High Field-like MR Images -- Deep Neural Network for QSM Background Field Removal -- RinQ Fingerprinting: Recurrence-informed Quantile Networks for Magnetic Resonance Fingerprinting -- RCA-U-Net: Residual Channel Attention U-Net for Fast Tissue Quantification in Magnetic Resonance Fingerprinting -- GANReDL: Medical Image enhancement using a generative adversarial network with real-order derivative induced loss functions -- Generation of 3D Brain MRI Using Auto-Encoding Generative Adversarial Networks -- Semi-Supervised VAE-GAN for Out-of-Sample Detection Applied to MRI Quality Control -- Disease-Image Specific Generative Adversarial Network for Brain Disease Diagnosis with Incomplete Multi-Modal Neuroimages -- Predicting the Evolution of White Matter Hyperintensities in Brain MRI using Generative Adversarial Networks and Irregularity Map -- CoCa-GAN: Common-feature-learning-based Context-aware Generative Adversarial Network for Glioma Grading -- Degenerative Adversarial NeuroImage Nets: Generating Images that Mimic Disease Progression -- Neuroimage Segmentation -- Scribble-based Hierarchical Weakly Supervised Learning for Brain Tumor Segmentation -- 3D Dilated Multi-Fiber Network for Real-time Brain Tumor Segmentation in MRI -- Refined-Segmentation R-CNN: A Two-stage Convolutional Neural Network for Punctate White Matter Lesion Segmentation in Preterm Infants -- VoteNet: A Deep Learning Label Fusion Method for Multi-Atlas Segmentation -- Weakly Supervised Brain Lesion Segmentation via Attentional Representation Learning -- Scalable Neural Architecture Search for 3D Medical Image Segmentation -- Unified Attentional Generative Adversarial Network for Brain Tumor Segmentation From Multimodal Unpaired Images -- High Resolution Medical Image Segmentation using Data-swapping Method -- X-Net: Brain Stroke Lesion Segmentation Based on Depthwise Separable Convolution and Long-range Dependencies -- Multi-View Semi-supervised 3D Whole Brain Segmentation with a Self-Ensemble Network -- CLCI-Net: Cross-Level Fusion and Context Inference Networks for Lesion Segmentation of Chronic Stroke -- Brain Segmentation from k-space with End-to-end Recurrent Attention Network -- Spatial Warping Network for 3D Segmentation of the Hippocampus in MR Images -- CompareNet: Anatomical Segmentation Network with Deep Non-local Label Fusion -- A Joint 3D+2D Fully Convolutional Framework for Subcortical Segmentation -- U-ReSNet: Ultimate coupling of Registration and Segmentation with deep Nets -- Generative adversarial network for segmentation of motion affected neonatal brain MRI -- Interactive deep editing framework for medical image segmentation -- Multiple Sclerosis Lesion Segmentation with Tiramisu and 2.5D Stacked Slices -- Improving Multi-Atlas Segmentation by Convolutional Neural Network Based Patch Error Estimation -- Unsupervised deep learning for Bayesian brain MRI segmentation -- Online atlasing using an iterative centroid -- ARS-Net: Adaptively Rectified Supervision Network for Automated 3D Ultrasound Image Segmentation -- Complete Fetal Head Compounding from Multi-View 3D Ultrasound -- SegNAS3D: Network Architecture Search with Derivative-Free Global Optimization for 3D Image Segmentation -- Overfitting of neural nets under class imbalance: Analysis and improvements for segmentation -- RSANet: Recurrent Slice-wise Attention Network for Multiple Sclerosis Lesion Segmentation -- Deep Cascaded Attention Networks for Multi-task Brain Tumor Segmentation -- Partially Reversible U-Net for Memory-Efficient Volumetric Image Segmentation -- 3DQ: Compact Quantized Neural Networks for Volumetric Whole Brain Segmentation -- Robust Multimodal Brain Tumor Segmentation via Feature Disentanglement and Gated Fusion -- Multi-task Attention-based Semi-supervised Learning for Medical Image Segmentation -- AssemblyNet: A Novel Deep Decision-Making Process for Whole Brain MRI Segmentation -- Automated Parcellation of the Cortex using Structural Connectome Harmonics -- Hierarchical parcellation of the cerebellum -- Intrinsic Patch-based Cortical Anatomical Parcellation using Graph Convolutional Neural Network on Surface Manifold -- Cortical Surface Parcellation using Spherical Convolutional Neural Networks -- A Soft STAPLE Algorithm Combined with Anatomical Knowledge -- Diffusion Weighted Magnetic Resonance Imaging -- Multi-Stage Image Quality Assessment of Diffusion MRI via Semi-Supervised Nonlocal Residual Networks -- Reconstructing High-Quality Diffusion MRI Data from Orthogonal Slice-Undersampled Data Using Graph Convolutional Neural Networks -- Surface-based Tracking of U-fibers in the Superficial White Matter -- Probing Brain Micro-Architecture by Orientation Distribution Invariant Identification of Diffusion Compartments -- Characterizing Non-Gaussian Diffusion in Heterogeneously Oriented Tissue Microenvironments -- Topographic Filtering of Tractograms as Vector Field Flows -- Enabling Multi-Shell b-Value Generalizability of Data-Driven Diffusion Models with Deep SHORE -- Super-Resolved q-Space Deep Learning -- Joint Identification of Network Hub Nodes by Multivariate Graph Inference -- Deep white matter analysis: fast, consistent tractography segmentation across populations and dMRI acquisitions -- Improved Placental Parameter Estimation Using Data-Driven Bayesian Modelling -- Optimal experimental design for biophysical modelling in multidimensional diffusion MRI -- DeepTract: A Probabilistic Deep Learning Framework for White Matter Fiber Tractography -- Fast and Scalable Optimal Transport for Brain Tractograms -- A hybrid deep learning framework for integrated segmentation and registration: evaluation on longitudinal white matter tract changes -- Constructing Consistent Longitudinal Brain Networks by Group-wise Graph Learning -- Functional Neuroimaging (fMRI) -- Multi-layer temporal network analysis reveals increasing temporal reachability and spreadability in the first two years of life -- A matched filter decomposition of fMRI into resting and task components -- Identification of Abnormal Circuit Dynamics in Major Depressive Disorder via Multiscale Neural Modeling of Resting-state fMRI -- Integrating Functional and Structural Connectivities via Diffusion-Convolution-Bilinear Neural Network -- Invertible Network for Classification and Biomarker Selection for ASD -- Integrating Neural Networks and Dictionary Learning for Multidimensional Clinical Characterizations from Functional Connectomics Data -- Revealing Functional Connectivity by Learning Graph Laplacian -- Constructing Multi-Scale Connectome Atlas by Learning Common Topology of Brain Networks -- Autism Classification Using Topological Features and Deep Learning: A Cautionary Tale -- Identify Hierarchical Structures from Task-based fMRI Data via Hybrid Spatiotemporal Neural Architecture Search Net -- A Deep Learning Framework for Noise Component Detection from Resting-state Functional MRI -- A Novel Graph Wavelet Model for Brain Multi-Scale Functional-structural Feature Fusion -- Combining Multiple Behavioral Measures and Multiple Connectomes via Multiway Canonical Correlation Analysis -- Decoding brain functional connectivity implicated in AD and MCI -- Interpretable Feature Learning Using Multi-Output Takagi-Sugeno-Kang Fuzzy System for Multi-center ASD Diagnosis -- Interpretable Multimodality Embedding Of Cerebral Cortex Using Attention Graph Network For Identifying Bipolar Disorder -- Miscellaneous Neuroimaging -- Doubly Weak Supervision of Deep Learning Models for Head CT -- Detecting Acute Strokes from Non-Contrast CT Scan Data Using Deep Convolutional Neural Networks -- FocusNet: Imbalanced Large and Small Organ Segmentation with an End-to-End Deep Neural Network for Head and Neck CT Images -- Regression-based Line Detection Network for Delineation of Largely Deformed Brain Midline -- Siamese U-Net with Healthy Template for Accurate Segmentation of Intracranial Hemorrhage -- Automated Infarct Segmentation from Follow-up Non-Contrast CT Scans in Patients with Acute Ischemic Stroke Using Dense Multi-Path Contextual Generative Adversarial Network -- Recurrent sub-volume analysis of head CT scans for the detection of intracranial hemorrhage -- Cephalometric Landmark Detection by Attentive Feature Pyramid Fusion and Regression-Voting. |
| Record Nr. | UNINA-9910349273803321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 : 22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part II / / edited by Dinggang Shen, Tianming Liu, Terry M. Peters, Lawrence H. Staib, Caroline Essert, Sean Zhou, Pew-Thian Yap, Ali Khan
| Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 : 22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part II / / edited by Dinggang Shen, Tianming Liu, Terry M. Peters, Lawrence H. Staib, Caroline Essert, Sean Zhou, Pew-Thian Yap, Ali Khan |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XXXVIII, 874 p.) |
| Disciplina |
006.6
006.37 616.0757 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Pattern recognition Artificial intelligence Health informatics Image Processing and Computer Vision Pattern Recognition Artificial Intelligence Health Informatics |
| ISBN | 3-030-32245-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Image Segmentation -- Searching Learning Strategy with Reinforcement Learning for 3D Medical Image Segmentation -- Comparative Evaluation of Hand-Engineered and Deep-Learned Features for Neonatal Hip Bone Segmentation in Ultrasound -- Unsupervised Quality Control of Image Segmentation based on Bayesian Learning -- One Network To Segment Them All: A General, Lightweight System for Accurate 3D Medical Image Segmentation -- 'Project & Excite' Modules for Segmentation of Volumetric Medical Scans -- Assessing Reliability and Challenges of Uncertainty Estimations for Medical Image Segmentation -- Learning Cross-Modal Deep Representations for Multi-Modal MR Image Segmentation -- Extreme Points Derived Confidence Map as a Cue For Class-Agnostic Segmentation Using Deep Neural Network -- Hetero-Modal Variational Encoder-Decoder for Joint Modality Completion and Segmentation -- Instance Segmentation from Volumetric Biomedical Images without Voxel-Wise Labeling -- Optimizing the Dice Score and Jaccard Index for Medical Image Segmentation: Theory & Practice -- Dual Adaptive Pyramid Network for Cross-Stain Histopathology Image Segmentation -- HD-Net: Hybrid Discriminative Network for Prostate Segmentation in MR Images -- PHiSeg: Capturing Uncertainty in Medical Image Segmentation -- Neural Style Transfer Improves 3D Cardiovascular MR Image Segmentation on Inconsistent Data -- Supervised Uncertainty Quantification for Segmentation with Multiple Annotations -- 3D Tiled Convolution for Effective Segmentation of Volumetric Medical Images -- Hyper-Pairing Network for Multi-Phase Pancreatic Ductal Adenocarcinoma Segmentation -- Statistical intensity- and shape-modeling to automate cerebrovascular segmentation from TOF-MRA data -- Segmentation of Vessels in Ultra High Frequency Ultrasound Sequences using Contextual Memory -- Accurate Esophageal Gross Tumor Volume Segmentation in PET/CT using Two-Stream Chained 3D Deep Network Fusion -- Mixed-Supervised Dual-Network for Medical Image Segmentation -- Fully Automated Pancreas Segmentation with Two-stage 3D Convolutional Neural Networks -- Globally Guided Progressive Fusion Network for 3D Pancreas Segmentation -- Automatic Segmentation of Muscle Tissue and Inter-muscular Fat in Thigh and Calf MRI Images -- Resource Optimized Neural Architecture Search for 3D Medical Image Segmentation -- Radiomics-guided GAN for Segmentation of Liver Tumor without Contrast Agents -- Liver Segmentation in Magnetic Resonance Imaging via Mean Shape Fitting with Fully Convolutional Neural Networks -- Unsupervised Domain Adaptation via Disentangled Representations: Application to Cross-Modality Liver Segmentation -- Automatic Segmentation of Vestibular Schwannoma from T2-Weighted MRI by Deep Spatial Attention with Hardness-Weighted Loss -- Learning Shape Representation on Sparse Point Clouds for Volumetric Image Segmentation -- Collaborative Multi-agent Learning for MR Knee Articular Cartilage Segmentation -- 3D U2-Net: A 3D Universal U-Net for Multi-Domain Medical Image Segmentation -- Impact of Adversarial Examples on Deep Learning Segmentation Models -- Multi-Resolution Path CNN with Deep Supervision for Intervertebral Disc Localization and Segmentation -- Automatic paraspinal muscle segmentation in patients with lumbar pathology using deep convolutional neural network -- Constrained Domain Adaptation for Segmentation -- Image Registration -- Image-and-Spatial Transformer Networks for Structure-Guided Image Registration -- Probabilistic Multilayer Regularization Network for Unsupervised 3D Brain Image Registration -- A deep learning approach to MR-less spatial normalization for tau PET images -- TopAwaRe: Topology-Aware Registration -- Multimodal Data Registration for Brain Structural Association Networks -- Dual-Stream Pyramid Registration Network -- A Cooperative Autoencoder for Population-Based Regularization of CNN Image Registration -- Conditional Segmentation in Lieu of Image Registration -- On the applicability of registration uncertainty -- DeepAtlas: Joint Semi-Supervised Learning of Image Registration and Segmentation -- Linear Time Invariant Model based Motion Correction (LiMo-Moco) of Dynamic Radial Contrast Enhanced MRI -- Incompressible image registration using divergence-conforming B-splines -- Cardiovascular Imaging -- Direct Quantification for Coronary Artery Stenosis Using Multiview Learning -- Bayesian Optimization on Large Graphs via a Graph Convolutional Generative Model: Application in Cardiac Model Personalization -- Discriminative Coronary Artery Tracking via 3D CNN in Cardiac CT Angiography -- Multi-modality Whole-Heart and Great Vessel Segmentation in Congenital Heart Disease using Deep Neural Networks and Graph Matching -- Harmonic Balance Techniques in Cardiovascular Fluid Mechanics -- Deep learning within a priori temporal feature spaces for large-scale dynamic MR image reconstruction: Application to 5-D cardiac MR Multitasking -- k-t NEXT: Dynamic MR Image Reconstruction Exploiting Spatio-temporal Correlations -- Model-based reconstruction for highly accelerated first-pass perfusion cardiac MRI -- Learning Shape Priors for Robust Cardiac MR Segmentation from Multi-view images -- Right Ventricle Segmentation in Short-Axis MRI Using A Shape Constrained Dense Connected U-net -- Self-Supervised Learning for Cardiac MR Image Segmentation by Anatomical Position Prediction -- A Fine-Grain Error Map Prediction and Segmentation Quality Assessment Framework for Whole-Heart Segmentation -- Cardiac Segmentation from LGE MRI Using Deep Neural Network Incorporating Shape and Spatial Priors -- Curriculum semi-supervised segmentation -- A Multi-modal Network for Cardiomyopathy Death Risk Prediction with CMR Images and Clinical Information -- 3D Cardiac Shape Prediction with Deep Neural Networks: Simultaneous Use of Images and Patient Metadata -- Discriminative Consistent Domain Generation for Semi-supervised Learning -- Uncertainty-aware Self-ensembling Model for Semi-supervised 3D Left Atrium Segmentation -- MSU-Net: Multiscale Statistical U-Net for Real-time 3D Cardiac MRI Video Segmentation -- The Domain Shift Problem of Medical Image Segmentation and Vendor-Adaptation by Unet-GAN -- Cardiac MRI Segmentation with Strong Anatomical Guarantees -- Decompose-and-Integrate Learning for Multi-class Segmentation in Medical Images -- Missing Slice Imputation in Population CMR Imaging via Conditional Generative Adversarial Nets -- Unsupervised Standard Plane Synthesis in Population Cine MRI via Cycle-Consistent Adversarial Networks -- Data Efficient Unsupervised Domain Adaptation for Cross-Modality Image Segmentation -- Recurrent Aggregation Learning for Multi-View Echocardiographic Sequences Segmentation -- Echocardiography View Classification Using Quality Transfer Star Generative Adversarial Networks -- Dual-view Joint Estimation of Left Ventricular Ejection Fraction with Uncertainty Modelling in Echocardiograms -- Frame Rate Up-Conversion in Echocardiography Using a Conditioned Variational Autoencoder and Generative Adversarial Model -- Annotation-Free Cardiac Vessel Segmentation via Knowledge Transfer from Retinal Images -- DeepAAA: clinically applicable and generalizable detection of abdominal aortic aneurysm using deep learning -- Texture-based classification of significant stenosis in CCTA multi-view images of coronary arteries -- Fourier Spectral Dynamic Data Assimilation: Interlacing CFD with 4D flow MRI -- Quality Control-Driven Image Segmentation Towards Reliable Automatic Image Analysis in Large-Scale Cardiovascular Magnetic Resonance Aortic Cine Imaging -- HFA-Net: 3D Cardiovascular Image Segmentation with Asymmetrical Pooling and Content-Aware Fusion -- Spectral CT based training dataset generation and augmentation for conventional CT vascular segmentation -- Context-Aware Inductive Bias Learning for Vessel Border Detection in Multi-modal Intracoronary Imaging -- Growth, Development, Atrophy and Progression -- Neural parameters estimation for brain tumor growth modeling -- Learning-Guided Infinite Network Atlas Selection for Predicting Longitudinal Brain Network Evolution from a Single Observation -- Deep Probabilistic Modeling of Glioma Growth -- Surface-Volume Consistent Construction of Longitudinal Atlases for the Early Developing Brains -- Variational Autoencoder for Regression: Application to Brain Aging Analysis -- Early Development of Infant Brain Complex Network -- Revealing Developmental Regionalization of Infant Cerebral Cortex Based on Multiple Cortical Properties -- Continually Modeling Alzheimer's Disease Progression via Deep Multi-Order Preserving Weight Consolidation -- Disease Knowledge Transfer across Neurodegenerative Diseases. |
| Record Nr. | UNINA-9910349273903321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 : 22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part V / / edited by Dinggang Shen, Tianming Liu, Terry M. Peters, Lawrence H. Staib, Caroline Essert, Sean Zhou, Pew-Thian Yap, Ali Khan
| Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 : 22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part V / / edited by Dinggang Shen, Tianming Liu, Terry M. Peters, Lawrence H. Staib, Caroline Essert, Sean Zhou, Pew-Thian Yap, Ali Khan |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XXXVI, 695 p. 387 illus., 286 illus. in color.) |
| Disciplina |
616.07540285
616.0757 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Pattern recognition Artificial intelligence Health informatics Image Processing and Computer Vision Pattern Recognition Artificial Intelligence Health Informatics |
| ISBN | 3-030-32254-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Computer Assisted Interventions -- Robust Cochlear Modiolar Axis Detection in CT -- Learning to Avoid Poor Images: Towards Task-aware C-arm Cone-beam CT Trajectories -- Optimizing Clearance of Bézier Spline Trajectories for Minimally-Invasive Surgery -- Direct Visual and Haptic Volume Rendering of Medical Data Sets for an Immersive Exploration in Virtual Reality -- Triplet Feature Learning on Endoscopic Video Manifold for Real-time Gastrointestinal Image Retargeting -- A Novel Endoscopic Navigation System: Simultaneous Endoscope and Radial Ultrasound Probe Tracking Without External Trackers -- An Extremely Fast and Precise Convolutional Neural Network for Recognition and Localization of Cataract Surgical Tools -- Semi-autonomous Robotic Anastomoses of Vaginal Cuffs using Marker Enhanced 3D Imaging and Path Planning -- Augmented Reality "X-Ray Vision" for Laparoscopic Surgery using Optical See-Through Head-Mounted Display -- Interactive Endoscopy: A Next-Generation, Streamlined User Interface for Lung Surgery Navigation -- Non-invasive Assessment of In Vivo Auricular Cartilage by Ultrashort Echo Time (UTE) T2* Mapping -- INN: Inflated Neural Networks for IPMN Diagnosis -- Development of an Multi-objective Optimized Planning Method for Microwave Liver Tumor Ablation -- Generating large labeled data sets for laparoscopic image processing tasks using unpaired image-to-image translation -- Mask-MCNet: Instance Segmentation in 3D Point Cloud of Intra-oral Scans -- Physics-based Deep Neural Network for Augmented Reality during Liver Surgery -- Detecting Cannabis-Associated Cognitive Impairment using Resting-state fNIRS -- Cross-Domain Conditional Generative Adversarial Networks for Stereoscopic Hyperrealism in Surgical Training -- A Free-view, 3D Gaze-Guided Robotic Scrub Nurse -- Haptic Modes for Multiparameter Control in Robotic Surgery -- Learning to Detect Collisions for Continuum Manipulators without a Prior Model -- Simulation of Balloon-Expandable Coronary Stent Apposition with Plastic Beam Elements -- Virtual Cardiac Surgical Planning through Hemodynamics Simulation and Design Optimization of Fontan Grafts -- 3D Modelling of the residual freezing for renal cryoablation simulation and prediction -- A generative model of hyperelastic strain energy density functions for real-time simulation of brain tissue deformation -- Variational Mandible Shape Completion for Virtual Surgical Planning -- Markerless Image-to-Face Registration for Untethered Augmented Reality in Head and Neck Surgery -- Towards a first mixed-reality first person point of view needle navigation system -- Concept-Centric Visual Turing Tests for Method Validation -- Transferring from ex-vivo to in-vivo: Instrument Localization in 3D Cardiac Ultrasound Using Pyramid-UNet with Hybrid Loss -- A Sparsely Distributed Intra-cardial Ultrasonic Array for Real-time Endocardial Mapping -- FetusMap: Fetal Pose Estimation in 3D Ultrasound -- Agent with Warm Start and Active Termination for Plane Localization in 3D Ultrasound -- Learning and Understanding Deep Spatio-Temporal Representations from Free-Hand Fetal Ultrasound Sweeps -- User guidance for point-of-care echocardiography using multi-task deep neural network -- Integrating 3D Geometry of Organ for Improving Medical Imaging Segmentation -- Estimating Reference Bony Shape Model for Personalized Surgical Reconstruction of Posttraumatic Facial Defects -- A New Approach of Predicting Facial Changes following Orthognathic Surgery using Realistic Lip Sliding Effect -- An Automatic Approach to Reestablish Final Dental Occlusion for 1-Piece Maxillary Orthognathic Surgery -- MIC meets CAI -- A Two-stage Framework for Real-time Guidewire Endpoint Localization -- Investigating the role of VR in a simulation-based medical planning system for coronary interventions -- Learned Full-sampling Reconstruction -- A deep regression model for seed localization in prostate brachytherapy -- Model-Based Surgical Recommendations for Optimal Placement of Epiretinal Implants -- Towards Multiple Instance Learning and Hermann Weyl's Discrepancy for Robust Image-Guided Bronchoscopic Intervention -- Learning Where to Look While Tracking Instruments in Robot-assisted Surgery -- Efficient Soft-Constrained Clustering for Group-Based Labeling -- Leveraging Other Datasets for Medical Imaging Classification: Evaluation of Transfer, Multi-task and Semi-supervised Learning -- Incorporating Temporal Prior from Motion Flow for Instrument Segmentation in Minimally Invasive Surgery Video -- Hard Frame Detection and Online Mapping for Surgical Phase Recognition -- Automated Surgical Activity Recognition with One Labeled Sequence -- Using 3D Convolutional Neural Networks to learn spatiotemporal features for automatic surgical gesture recognition in video -- Surgical Skill Assessment on In-Vivo Clinical Data via the Clearness of Operating Field -- Graph Neural Network for Interpreting Task-fMRI Biomarkers -- Achieving Accurate Segmentation of Nasopharyngeal Carcinoma in MR Images through Recurrent Attention -- Brain Dynamics Through the Lens of Statistical Mechanics by Unifying Structure and Function -- Synthesis and Inpainting-based MR-CT Registration for Image-Guided Thermal Ablation of Liver Tumors -- CFEA: Collaborative Feature Ensembling Adaptation for Domain Adaptation in Unsupervised Optic Disc and Cup Segmentation -- Gastric cancer detection from endoscopic images using synthesis by GAN -- Deep Local-Global Refinement Network for Stent Analysis in IVOCT Images -- Generalized Non-Rigid Point Set Registration with Hybrid Mixture Models Considering Anisotropic Positional Uncertainties -- Mixed-Supervision Multilevel GAN for Image Quality Enhancement -- Combined Learning for Similar Tasks with Domain-Switching Networks -- Real-time 3D reconstruction of colonoscopic surfaces for determining missing regions -- Human Pose Estimation on Privacy-Preserving Low-Resolution Depth Images -- A Mesh-Aware Ball-Pivoting Algorithm for Generating the Virtual Arachnoid Mater -- Attenuation Imaging with Pulse-Echo Ultrasound based on an Acoustic Reflector -- SWTV-ACE: Spatially Weighted Regularization based Attenuation Coefficient Estimation Method for Hepatic Steatosis Detection -- Deep Learning-based Universal Beamformer for Ultrasound Imaging -- Towards whole placenta segmentation at late gestation using multi-view ultrasound images -- Single Shot Needle Tip Localization in 2D Ultrasound -- Discriminative Correlation Filter Network for Robust Landmark Tracking in Ultrasound Guided Intervention -- Echocardiography Segmentation by Quality Translation using Anatomically Constrained CycleGAN -- Matwo-CapsNet: a Multi-Label Semantic Segmentation Capsules Network -- LumiPath - Towards Real-time Physically-based Rendering on Embedded Devices -- An Integrated Multi-Physics Finite Element Modeling Framework for Deep Brain Stimulation: Preliminary Study on Impact of Brain Shift on Neuronal Pathways. |
| Record Nr. | UNINA-9910349273603321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 : 22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part VI / / edited by Dinggang Shen, Tianming Liu, Terry M. Peters, Lawrence H. Staib, Caroline Essert, Sean Zhou, Pew-Thian Yap, Ali Khan
| Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 : 22nd International Conference, Shenzhen, China, October 13–17, 2019, Proceedings, Part VI / / edited by Dinggang Shen, Tianming Liu, Terry M. Peters, Lawrence H. Staib, Caroline Essert, Sean Zhou, Pew-Thian Yap, Ali Khan |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XXXVIII, 860 p. 476 illus., 308 illus. in color.) |
| Disciplina |
616.07540285
616.0757 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Pattern recognition Artificial intelligence Health informatics Image Processing and Computer Vision Pattern Recognition Artificial Intelligence Health Informatics |
| ISBN | 3-030-32226-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Computed Tomography -- Multi-Scale Coarse-to-Fine Segmentation for Screening Pancreatic Ductal Adenocarcinoma -- MVP-Net: Multi-view FPN with Position-aware Attention for Deep Universal Lesion Detection -- Spatial-Frequency Non-Local Convolutional LSTM Network for pRCC classification -- BCD-Net for Low-dose CT Reconstruction: Acceleration, Convergence, and Generalization -- Abdominal Adipose Tissue Segmentation in MRI with Double Loss Function Collaborative Learning -- Closing the Gap between Deep and Conventional Image Registration using Probabilistic Dense Displacement Networks -- Generating Pareto optimal dose distributions for radiation therapy treatment planning -- PAN: Projective Adversarial Network for Medical Image Segmentation -- Generative Mask Pyramid Network for CT/CBCT Metal Artifact Reduction with Joint Projection-Sinogram Correction -- Multi-Class Gradient Harmonized Dice Loss with Application to Knee MR Image Segmentation -- LSRC: A Long-Short Range Context-Fusing Framework for Automatic 3D Vertebra Localization -- Contextual Deep Regression Network for Volume Estimation in Orbital CT -- Multi-scale GANs for Memory-efficient Generation of High Resolution Medical Images -- Deep Learning based Metal Artifacts Reduction in post-operative Cochlear Implant CT Imaging -- ImHistNet: Learnable Image Histogram Based DNN with Application to Noninvasive Determination of Carcinoma Grades in CT Scans -- DPA-DenseBiasNet: Semi-supervised 3D Fine Renal Artery Segmentation with Dense Biased Network and Deep Priori Anatomy -- Semi-supervised Segmentation of Liver Using Adversarial Learning with Deep Atlas Prior -- Pairwise Semantic Segmentation via Conjugate Fully Convolutional Network -- Unsupervised Deformable Image Registration Using Cycle-Consistent CNN -- Volumetric Attention for 3D Medical Image Segmentation and Detection -- Improving Deep Lesion Detection Using 3D Contextual and Spatial Attention -- MULAN: Multitask Universal Lesion Analysis Network for Joint Lesion Detection, Tagging, and Segmentation -- Artifact Disentanglement Network for Unsupervised Metal Artifact Reduction -- AirwayNet: A Voxel-Connectivity Aware Approach for Accurate Airway Segmentation Using Convolutional Neural Networks -- Integrating cross-modality hallucinated MRI with CT to aid mediastinal lung tumor segmentation -- Bronchus Segmentation and Classification by Neural Networks and Linear Programming -- Unsupervised Segmentation of Micro-CT Images of Lung Cancer Specimen Using Deep Generative Models -- Normal appearance autoencoder for lung cancer detection and segmentation -- mlVIRNET: Multilevel Variational Image Registration Network -- NoduleNet: Decoupled False Positive Reduction for Pulmonary Nodule Detection and Segmentation -- Encoding CT Anatomy Knowledge for Unpaired Chest X-ray Image Decomposition -- Targeting Precision with Data Augmented Samples in Deep Learning -- Pulmonary Vessel Segmentation based on Orthogonal Fused U-Net++ of Chest CT Images -- Attentive CT Lesion Detection Using Deep Pyramid Inference with Multi-Scale Booster -- Deep Variational Networks with Exponential Weighting for Learning Computed Tomography -- R2-Net: Recurrent and Recursive Network for Sparse-view CT Artifacts Removal -- Stereo-Correlation and Noise-Distribution Aware ResVoxGAN for Dense Slices Reconstruction and Noise Reduction in Thick Low-Dose CT -- Harnessing 2D Networks and 3D Features for Automated Pancreas Segmentation from Volumetric CT Images -- Tubular Structure Segmentation Using Spatial Fully Connected Network With Radial Distance Loss for 3D Medical Images -- Bronchial Cartilage Assessment with Model-Based GAN Regressor -- Adversarial optimization for joint registration and segmentation in prostate CT radiotherapy -- Probabilistic Point Cloud Reconstructions for Vertebral Shape Analysis -- Automatically Localizing a Large Set of Spatially Correlated Key Points: A Case Study in Spine Imaging -- Permutohedral Attention Module for Efficient Non-Local Neural Networks -- Improving RetinaNet for CT Lesion Detection with Dense Masks from Weak RECIST Labels -- X-ray Imaging -- PRSNet: Part Relation and Selection Network for Bone Age Assessment -- Mask Embedding for Realistic High-resolution Medical Image Synthesis -- TUNA-Net: Task-oriented UNsupervised Adversarial Network for Disease Recognition in Cross-Domain Chest X-rays -- Misshapen Pelvis Landmark Detection by Spatial Local Correlation Mining for Diagnosing Developmental Dysplasia of the Hip -- Adversarial Policy Gradient for Deep Learning Image Augmentation -- Weakly Supervised ROI Mining Toward Universal Fracture Detection in Pelvic X-ray -- Learning from Suspected Target: Bootstrapping Performance for Breast Cancer Detection in Mammography -- From Unilateral to Bilateral Learning: Detecting Mammogram Mass with Contrasted Bilateral Network -- Signed Laplacian Deep Learning with Adversarial Augmentation for Improved Mammography Diagnosis -- Uncertainty measurements for the reliable classification of mammograms -- GraphX$^{NET}-$ Chest X-Ray Classification Under Extreme Minimal Supervision -- 3DFPN-HS2: 3D Feature Pyramid Network Based High Sensitivity and Specificity Pulmonary Nodule Detection -- Automated detection and type classification of central venous catheters in chest X-rays -- A Comprehensive Framework for Accurate Classification of Pulmonary Nodules -- Hand Pose Estimation for Pediatric Bone Age Assessment -- An Attention-Guided Deep Regression Model for Landmark Detection in Cephalograms -- Learning-based X-ray Image Denoising utilizing Model-based Image Simulations -- LVC-Net: Medical image segmentation with noisy label based on Local Visual Cues -- Unsupervised Cone-Beam Computed Tomography (CBCT) segmentation based on adversarial learning domain adaptation -- Pick-and-Learn: Automatic Quality Evaluation for Noisy-Labeled Image Segmentation -- Anatomical Priors for Image Segmentation via Post-Processing with Denoising Autoencoders -- Simultaneous Lung Field Detection and Segmentation for Pediatric ChestRadiographs -- Deep Esophageal Clinical Target Volume Delineation using Encoded 3D Spatial Context of Tumor, Lymph Nodes, and Organs At Risk -- Weakly Supervised Segmentation Framework with Uncertainty: A Study on Pneumothorax Segmentation in Chest X-ray -- Multi-task Localization and Segmentation for X-ray Guided Planning in Knee Surgery -- Towards fully automatic X-ray to CT registration -- Adaptive image-feature learning for disease classification using inductive graph networks -- How to learn from unlabeled volume data: Self-Supervised 3D Context Feature Learning -- Probabilistic Radiomics: Ambiguous Diagnosis with Controllable Shape Analysis -- Extract Bone Parts without Human Prior: End-to-end Convolutional Neural Network for Pediatric Bone Age Assessment -- Quantifying and Leveraging Classification Uncertainty for Chest Radiograph Assessment -- Adversarial regression training for visualizing the progression of chronic obstructive pulmonary disease with chest x-rays -- Medical-based Deep Curriculum Learning for Improved Fracture Classification -- Realistic Breast Mass Generation through BIRADS Category -- Learning from Longitudinal Mammography Studies -- Automated Radiology Report Generation via Multi-view Image Fusion and Medical Concept Enrichment -- Multi-label Thoracic Disease Image Classification with Cross-attention Networks -- InfoMask: Masked Variational Latent Representation to Localize Chest Disease -- Longitudinal Change Detection on Chest X-rays using Geometric Correlation Maps -- Adversarial Pulmonary Pathology Translation for Pairwise Chest X-ray Data Augmentation -- Semi-Supervised Learning by Disentangling and Self-Ensembling over Stochastic Latent Space -- An Automated Cobb Angle Estimation Method Using Convolutional Neural Network with Area Limitation -- Endotracheal Tube Detection and Segmentation in Chest Radiographs using Synthetic Data -- Learning Interpretable Features via Adversarially Robust Optimization -- Synthesize Mammogram from Digital Breast Tomosynthesis with Gradient Guided cGANs -- Semi-supervised Medical Image Segmentation via Learning Consistency under Transformations -- Improved Inference via Deep Input Transfer -- Neural Architecture Search for Adversarial Medical Image Segmentation -- MeshSNet: Deep Multi-Scale Mesh Feature Learning for End-to-End Tooth Labeling on 3D Dental Surfaces -- Improving Robustness of Medical Image Diagnosis with Denoising Convolutional Neural Networks. |
| Record Nr. | UNINA-9910349274103321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
