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Graph Learning in Medical Imaging [[electronic resource] ] : First International Workshop, GLMI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings / / edited by Daoqiang Zhang, Luping Zhou, Biao Jie, Mingxia Liu
| Graph Learning in Medical Imaging [[electronic resource] ] : First International Workshop, GLMI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings / / edited by Daoqiang Zhang, Luping Zhou, Biao Jie, Mingxia Liu |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (IX, 182 p. 87 illus., 68 illus. in color.) |
| Disciplina | 006.3 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Artificial intelligence
Optical data processing Pattern recognition Application software Artificial Intelligence Image Processing and Computer Vision Pattern Recognition Computer Appl. in Social and Behavioral Sciences |
| ISBN | 3-030-35817-8 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Graph Hyperalignment for Multi-Subject fMRI Functional Alignment -- Interactive 3D Segmentation Editing and Refinement via Gated Graph Neural Networks -- Adaptive Thresholding of Functional Connectivity Networks for fMRI-based Brain Disease Analysis -- Graph-kernel-based Multi-task Structured Feature Selection on Multi-level Functional Connectivity Networks for Brain Disease Classification -- Linking convolutional neural networks with graph convolutional networks: application in pulmonary artery-vein separation -- Comparative Analysis of Magnetic Resonance Fingerprinting Dictionaries via Dimensionality Reduction -- Learning Deformable Point Set Registration with Regularized Dynamic Graph CNNs for Large Lung Motion in COPD Patients -- Graph Convolutional Networks for Coronary Artery Segmentation in Cardiac CT Angiography -- Triplet Graph Convolutional Network forMulti-scale Analysis of Functional Connectivityusing Functional MRI -- Multi-Scale Graph Convolutional Network for Mild Cognitive Impairment Detection -- DeepBundle: Fiber Bundle Parcellation With Graph CNNs -- Identification of Functional Connectivity Features in Depression Subtypes Using a Data-Driven Approach -- Movie-watching fMRI Reveals Inter-subject Synchrony Alteration in Functional Brain Activity in ADHD -- Weakly- and Semi- Supervised Graph CNN for identifying Basal Cell Carcinoma on Pathological images -- Geometric Brain Surface Network For Brain Cortical Parcellation -- Automatic Detection of Craniomaxillofacial Anatomical Landmarks on CBCT Images using 3D Mask R-CNN -- Discriminative-Region-Aware Residual Network for Adolescent Brain Structure and Cognitive Development Analysis -- Graph Modeling for Identifying Breast Tumor Located in Dense Background of a Mammogram -- OCD Diagnosis via Smoothing Sparse Network and Stacked Sparse Auto-Encoder Learning -- A Longitudinal MRI Study of Amygdala and Hippocampal Subfields for Infants with Risk of Autism -- CNS: CycleGAN-assisted Neonatal Segmentation Model for Cross-Datasets. |
| Record Nr. | UNISA-996466431003316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Graph Learning in Medical Imaging : First International Workshop, GLMI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings / / edited by Daoqiang Zhang, Luping Zhou, Biao Jie, Mingxia Liu
| Graph Learning in Medical Imaging : First International Workshop, GLMI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings / / edited by Daoqiang Zhang, Luping Zhou, Biao Jie, Mingxia Liu |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (IX, 182 p. 87 illus., 68 illus. in color.) |
| Disciplina | 006.3 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Artificial intelligence
Optical data processing Pattern recognition Application software Artificial Intelligence Image Processing and Computer Vision Pattern Recognition Computer Appl. in Social and Behavioral Sciences |
| ISBN | 3-030-35817-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Graph Hyperalignment for Multi-Subject fMRI Functional Alignment -- Interactive 3D Segmentation Editing and Refinement via Gated Graph Neural Networks -- Adaptive Thresholding of Functional Connectivity Networks for fMRI-based Brain Disease Analysis -- Graph-kernel-based Multi-task Structured Feature Selection on Multi-level Functional Connectivity Networks for Brain Disease Classification -- Linking convolutional neural networks with graph convolutional networks: application in pulmonary artery-vein separation -- Comparative Analysis of Magnetic Resonance Fingerprinting Dictionaries via Dimensionality Reduction -- Learning Deformable Point Set Registration with Regularized Dynamic Graph CNNs for Large Lung Motion in COPD Patients -- Graph Convolutional Networks for Coronary Artery Segmentation in Cardiac CT Angiography -- Triplet Graph Convolutional Network forMulti-scale Analysis of Functional Connectivityusing Functional MRI -- Multi-Scale Graph Convolutional Network for Mild Cognitive Impairment Detection -- DeepBundle: Fiber Bundle Parcellation With Graph CNNs -- Identification of Functional Connectivity Features in Depression Subtypes Using a Data-Driven Approach -- Movie-watching fMRI Reveals Inter-subject Synchrony Alteration in Functional Brain Activity in ADHD -- Weakly- and Semi- Supervised Graph CNN for identifying Basal Cell Carcinoma on Pathological images -- Geometric Brain Surface Network For Brain Cortical Parcellation -- Automatic Detection of Craniomaxillofacial Anatomical Landmarks on CBCT Images using 3D Mask R-CNN -- Discriminative-Region-Aware Residual Network for Adolescent Brain Structure and Cognitive Development Analysis -- Graph Modeling for Identifying Breast Tumor Located in Dense Background of a Mammogram -- OCD Diagnosis via Smoothing Sparse Network and Stacked Sparse Auto-Encoder Learning -- A Longitudinal MRI Study of Amygdala and Hippocampal Subfields for Infants with Risk of Autism -- CNS: CycleGAN-assisted Neonatal Segmentation Model for Cross-Datasets. |
| Record Nr. | UNINA-9910357848303321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Machine learning in medical imaging : 11th International Workshop, MLMI 2020, held in conjunction with MICCAI 2020, Lima, Peru, October 4, 2020, Proceedings / / Mingxia Liu [and tree others], editors
| Machine learning in medical imaging : 11th International Workshop, MLMI 2020, held in conjunction with MICCAI 2020, Lima, Peru, October 4, 2020, Proceedings / / Mingxia Liu [and tree others], editors |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2020] |
| Descrizione fisica | 1 online resource (XV, 686 p. 402 illus., 230 illus. in color.) |
| Disciplina | 006.31 |
| Collana | Lecture notes in computer science |
| Soggetto topico | Machine learning |
| ISBN | 3-030-59861-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Temporal-Adaptive Graph Convolutional Network for Automated Identification of Major Depressive Disorder with Resting-State fMRI -- Error Attention Interactive Segmentation of Medical Images through Matting and Fusion -- A Novel fMRI Representation Learning Framework with GAN -- Semi-supervised Segmentation with Self-Training Based on Quality Estimation and Refinement -- 3D Segmentation Networks for Excessive Numbers of Classes: Distinct Bone Segmentation in Upper Bodies -- Super Resolution of Arterial Spin Labeling MR Imaging Using Unsupervised Multi-Scale Generative Adversarial Network -- Self-Recursive Contextual Network for Unsupervised 3D Medical Image Registration -- Automated Tumor Proportion Scoring for Assessment of PD-L1 Expression Based on Multi-Stage Ensemble Strategy -- Uncertainty Quantification in Medical Image Segmentation with Normalizing Flows -- Out-of-Distribution Detection for Skin Lesion Images with Deep Isolation Forest -- A 3D+2D CNN Approach Incorporating Boundary Loss for Stroke Lesion Segmentation -- Linking Adolescent Brain MRI to Obesity via Deep Multi-cue Regression Network -- Robust Multiple Sclerosis Lesion Inpainting with Edge Prior -- Segmentation to Label: Automatic Coronary Artery Labeling from Mask Parcellation -- GSR-Net: Graph Super-Resolution Network for Predicting High-Resolution from Low-Resolution Functional Brain Connectomes -- Anatomy-Aware Cardiac Motion Estimation -- Division and Fusion: Rethink Convolutional Kernels for 3D Medical Image Segmentation -- LDGAN: Longitudinal-Diagnostic Generative Adversarial Network for Disease Progression Prediction with Missing Structural MRI -- Unsupervised MRI Homogenization: Application to Pediatric Anterior Visual Pathway Segmentation -- Boundary-aware Network for Kidney Tumor Segmentation -- O-Net: An Overall Convolutional Network for Segmentation Tasks -- Label-Driven Brain Deformable Registration Using Structural Similarity and Nonoverlap Constraints -- EczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis -- Deep Distance Map Regression Network with Shape-aware Loss for Imbalanced Medical Image Segmentation -- Joint Appearance-Feature Domain Adaptation: Application to QSM Segmentation Transfer -- Exploring Functional Difference between Gyri and Sulci via Region-Specific 1D Convolutional Neural Networks -- Detection of Ischemic Infarct Core in Non-Contrast Computed Tomography -- Bayesian Neural Networks for Uncertainty Estimation of Imaging Biomarkers -- Extended Capture Range of Rigid 2D/3D Registration by Estimating Riemannian Pose Gradients -- Structural Connectivity Enriched Functional Brain Network using Simplex Regression with GraphNet -- Constructing High-Order Dynamic Functional Connectivity Networks from Resting-State fMRI for Brain Dementia Identification -- Multi-tasking Siamese Networks for Breast Mass Detection using Dual-view Mammogram Matching -- 3D Volume Reconstruction from Single Lateral X-ray Image via Cross-Modal Discrete Embedding Transition -- Cleft Volume Estimation and Maxilla Completion Using Cascaded Deep Neural Networks -- A Deep Network for Joint Registration and Reconstruction of Images with Pathologies -- Learning Conditional Deformable Shape Templates for Brain Anatomy -- Demographic-Guided Attention in Recurrent Neural Networks for Modeling Neuropathophysiological Heterogeneity -- Unsupervised Learning for Spherical Surface Registration -- Anatomy-guided Convolutional Neural Network for Motion Correction in Fetal Brain MRI -- Gyral Growth Patterns of Macaque Brains Revealed by Scattered Orthogonal Nonnegative Matrix Factorization -- Inhomogeneity Correction in Magnetic Resonance Images Using Deep Image Priors -- Hierarchical and Robust Pathology Image Reading for High-Throughput Cervical Abnormality Screening -- Importance Driven Continual Learning for Segmentation Across Domains -- RDCNet: Instance segmentation with a minimalist recurrent residual network -- Automatic Segmentation of Achilles Tendon Tissues using Deep Convolutional Neural Network -- An End to End System for Measuring Axon Growth -- Interwound Structural and Functional Difference Between Preterm and Term Infant Brains Revealed by Multi-view CCA -- Graph Convolutional Network Based Point Cloud for Head and Neck Vessel Labeling -- Unsupervised Learning-based Nonrigid Registration of High Resolution Histology Images -- Additive Angular Margin for Few Shot Learning to Classify Clinical Endoscopy Images -- Extracting and Leveraging Nodule Features with Lung Inpainting for Local Feature Augmentation -- Gambling Adversarial Nets for Hard Sample Mining and Structured Prediction: Application in Ultrasound Thyroid Nodule Segmentation -- Mammographic Image Conversion between Source and Target Acquisition Systems using CGAN -- An End-to-End learnable Flow Regularized Model for Brain Tumor Segmentation -- Neural Architecture Search for Microscopy Cell Segmentation -- Classification of Ulcerative Colitis Severity in Colonoscopy Videos Using Vascular Pattern Detection -- Predicting Catheter Ablation Outcomes from Heart Rhythm Time-series: Less Is More -- AdaBoosted Deep Ensembles: Getting Maximum Performance Out of Small Training Datasets -- Cross-Task Representation Learning for Anatomical Landmark Detection -- Cycle Ynet: Semi-supervised Tracking of 3D Anatomical Landmarks -- Learning Hierarchical Semantic Correspondence and Gland Instance Segmentation -- Open-Set Recognition for Skin Lesions using Dermoscopic Images -- End-to-End Coordinate Regression Model with Attention-Guided Mechanism for Landmark Localization in 3D Medical Images -- Enhanced MRI Reconstruction Network using Neural Architecture Search -- Learning Invariant Feature Representation to Improve Generalization across Chest X-ray Datasets -- Noise-aware Standard-dose PET Reconstruction Using General and Adaptive Robust Loss -- Semi-supervised Transfer Learning for Infant Cerebellum Tissue Segmentation -- Informative Feature-guided Siamese Network for Early Diagnosis of ASD. |
| Record Nr. | UNINA-9910427710503321 |
| Cham, Switzerland : , : Springer, , [2020] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Machine learning in medical imaging : 11th International Workshop, MLMI 2020, held in conjunction with MICCAI 2020, Lima, Peru, October 4, 2020, Proceedings / / Mingxia Liu [and tree others], editors
| Machine learning in medical imaging : 11th International Workshop, MLMI 2020, held in conjunction with MICCAI 2020, Lima, Peru, October 4, 2020, Proceedings / / Mingxia Liu [and tree others], editors |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2020] |
| Descrizione fisica | 1 online resource (XV, 686 p. 402 illus., 230 illus. in color.) |
| Disciplina | 006.31 |
| Collana | Lecture notes in computer science |
| Soggetto topico | Machine learning |
| ISBN | 3-030-59861-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Temporal-Adaptive Graph Convolutional Network for Automated Identification of Major Depressive Disorder with Resting-State fMRI -- Error Attention Interactive Segmentation of Medical Images through Matting and Fusion -- A Novel fMRI Representation Learning Framework with GAN -- Semi-supervised Segmentation with Self-Training Based on Quality Estimation and Refinement -- 3D Segmentation Networks for Excessive Numbers of Classes: Distinct Bone Segmentation in Upper Bodies -- Super Resolution of Arterial Spin Labeling MR Imaging Using Unsupervised Multi-Scale Generative Adversarial Network -- Self-Recursive Contextual Network for Unsupervised 3D Medical Image Registration -- Automated Tumor Proportion Scoring for Assessment of PD-L1 Expression Based on Multi-Stage Ensemble Strategy -- Uncertainty Quantification in Medical Image Segmentation with Normalizing Flows -- Out-of-Distribution Detection for Skin Lesion Images with Deep Isolation Forest -- A 3D+2D CNN Approach Incorporating Boundary Loss for Stroke Lesion Segmentation -- Linking Adolescent Brain MRI to Obesity via Deep Multi-cue Regression Network -- Robust Multiple Sclerosis Lesion Inpainting with Edge Prior -- Segmentation to Label: Automatic Coronary Artery Labeling from Mask Parcellation -- GSR-Net: Graph Super-Resolution Network for Predicting High-Resolution from Low-Resolution Functional Brain Connectomes -- Anatomy-Aware Cardiac Motion Estimation -- Division and Fusion: Rethink Convolutional Kernels for 3D Medical Image Segmentation -- LDGAN: Longitudinal-Diagnostic Generative Adversarial Network for Disease Progression Prediction with Missing Structural MRI -- Unsupervised MRI Homogenization: Application to Pediatric Anterior Visual Pathway Segmentation -- Boundary-aware Network for Kidney Tumor Segmentation -- O-Net: An Overall Convolutional Network for Segmentation Tasks -- Label-Driven Brain Deformable Registration Using Structural Similarity and Nonoverlap Constraints -- EczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis -- Deep Distance Map Regression Network with Shape-aware Loss for Imbalanced Medical Image Segmentation -- Joint Appearance-Feature Domain Adaptation: Application to QSM Segmentation Transfer -- Exploring Functional Difference between Gyri and Sulci via Region-Specific 1D Convolutional Neural Networks -- Detection of Ischemic Infarct Core in Non-Contrast Computed Tomography -- Bayesian Neural Networks for Uncertainty Estimation of Imaging Biomarkers -- Extended Capture Range of Rigid 2D/3D Registration by Estimating Riemannian Pose Gradients -- Structural Connectivity Enriched Functional Brain Network using Simplex Regression with GraphNet -- Constructing High-Order Dynamic Functional Connectivity Networks from Resting-State fMRI for Brain Dementia Identification -- Multi-tasking Siamese Networks for Breast Mass Detection using Dual-view Mammogram Matching -- 3D Volume Reconstruction from Single Lateral X-ray Image via Cross-Modal Discrete Embedding Transition -- Cleft Volume Estimation and Maxilla Completion Using Cascaded Deep Neural Networks -- A Deep Network for Joint Registration and Reconstruction of Images with Pathologies -- Learning Conditional Deformable Shape Templates for Brain Anatomy -- Demographic-Guided Attention in Recurrent Neural Networks for Modeling Neuropathophysiological Heterogeneity -- Unsupervised Learning for Spherical Surface Registration -- Anatomy-guided Convolutional Neural Network for Motion Correction in Fetal Brain MRI -- Gyral Growth Patterns of Macaque Brains Revealed by Scattered Orthogonal Nonnegative Matrix Factorization -- Inhomogeneity Correction in Magnetic Resonance Images Using Deep Image Priors -- Hierarchical and Robust Pathology Image Reading for High-Throughput Cervical Abnormality Screening -- Importance Driven Continual Learning for Segmentation Across Domains -- RDCNet: Instance segmentation with a minimalist recurrent residual network -- Automatic Segmentation of Achilles Tendon Tissues using Deep Convolutional Neural Network -- An End to End System for Measuring Axon Growth -- Interwound Structural and Functional Difference Between Preterm and Term Infant Brains Revealed by Multi-view CCA -- Graph Convolutional Network Based Point Cloud for Head and Neck Vessel Labeling -- Unsupervised Learning-based Nonrigid Registration of High Resolution Histology Images -- Additive Angular Margin for Few Shot Learning to Classify Clinical Endoscopy Images -- Extracting and Leveraging Nodule Features with Lung Inpainting for Local Feature Augmentation -- Gambling Adversarial Nets for Hard Sample Mining and Structured Prediction: Application in Ultrasound Thyroid Nodule Segmentation -- Mammographic Image Conversion between Source and Target Acquisition Systems using CGAN -- An End-to-End learnable Flow Regularized Model for Brain Tumor Segmentation -- Neural Architecture Search for Microscopy Cell Segmentation -- Classification of Ulcerative Colitis Severity in Colonoscopy Videos Using Vascular Pattern Detection -- Predicting Catheter Ablation Outcomes from Heart Rhythm Time-series: Less Is More -- AdaBoosted Deep Ensembles: Getting Maximum Performance Out of Small Training Datasets -- Cross-Task Representation Learning for Anatomical Landmark Detection -- Cycle Ynet: Semi-supervised Tracking of 3D Anatomical Landmarks -- Learning Hierarchical Semantic Correspondence and Gland Instance Segmentation -- Open-Set Recognition for Skin Lesions using Dermoscopic Images -- End-to-End Coordinate Regression Model with Attention-Guided Mechanism for Landmark Localization in 3D Medical Images -- Enhanced MRI Reconstruction Network using Neural Architecture Search -- Learning Invariant Feature Representation to Improve Generalization across Chest X-ray Datasets -- Noise-aware Standard-dose PET Reconstruction Using General and Adaptive Robust Loss -- Semi-supervised Transfer Learning for Infant Cerebellum Tissue Segmentation -- Informative Feature-guided Siamese Network for Early Diagnosis of ASD. |
| Record Nr. | UNISA-996418287903316 |
| Cham, Switzerland : , : Springer, , [2020] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Machine Learning in Medical Imaging [[electronic resource] ] : 10th International Workshop, MLMI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings / / edited by Heung-Il Suk, Mingxia Liu, Pingkun Yan, Chunfeng Lian
| Machine Learning in Medical Imaging [[electronic resource] ] : 10th International Workshop, MLMI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings / / edited by Heung-Il Suk, Mingxia Liu, Pingkun Yan, Chunfeng Lian |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XVIII, 695 p. 310 illus., 245 illus. in color.) |
| Disciplina | 616.07540285 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Artificial intelligence Image Processing and Computer Vision Artificial Intelligence |
| ISBN | 3-030-32692-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | rain MR Image Segmentation in Small Dataset with Adversarial Defense and Task Reorganization -- Spatial Regularized Classification Network for Spinal Dislocation Diagnosis -- Globally-Aware Multiple Instance Classifier for Breast Cancer Screening -- Advancing Pancreas Segmentation in Multi-protocol MRI Volumes using Hausdorff-Sine Loss Function -- WSI-Net: Branch-based and Hierarchy-aware Network for Segmentation and Classification of Breast Histopathological Whole-slide Images -- Lesion Detection with Deep Aggregated 3D Contextual Feature and Auxiliary Information -- MSAFusionNet: Multiple Subspace Attention Based Deep Multi-modal Fusion Network -- DCCL: A Benchmark for Cervical Cytology Analysis -- Smartphone-Supported Malaria Diagnosis Based on Deep Learning -- Children's Neuroblastoma Segmentation using Morphological Features -- GFD Faster R-CNN: Gabor Fractal DenseNet Faster R-CNN for automatic detection of esophageal abnormalities in endoscopic images -- Deep Active Lesion Segmentation -- Infant Brain Deformable Registration Using Global and Local Label-Driven Deep Regression Learning -- A Relation Hashing Network Embedded with Prior Features for Skin Lesion Classification -- End-to-End Adversarial Shape Learning for Abdomen Organ Deep Segmentation -- Privacy-preserving Federated Brain Tumour Segmentation -- Residual Attention Generative Adversarial Networks for Nuclei Detection on Routine Colon Cancer Histology Images -- Semi-Supervised Multi-Task Learning With Chest X-Ray Images -- Novel Bi-directional Images Synthesis based on WGAN-GP with GMM-based Noise Generation -- Pseudo-labeled bootstrapping and multi-stage transfer learning for the classification and localization of dysplasia in Barrett’s Esophagus -- Anatomy-Aware Self-supervised Fetal MRI Synthesis from Unpaired Ultrasound Images -- Boundary Aware Networks for Medical Image Segmentation -- Automatic Rodent Brain MRI Lesion Segmentation with Fully Convolutional Networks -- Morphological Simplification of Brain MR Images by Deep Learning for Facilitating Deformable Registration -- Joint Shape Representation and Classification for Detecting PDAC -- FusionNet: Incorporating Shape and Texture for Abnormality Detection in 3D Abdominal CT Scans -- Weakly supervised segmentation by a deep geodesic prior -- Ultrasound Liver Fibrosis Diagnosis using Multi-indicator guided Deep Neural Networks -- Correspondence-Steered Volumetric Descriptor Learning Using Deep Functional Maps -- Sturm: Sparse Tubal-Regularized Multilinear Regression for fMRI -- Improving Whole-Brain Neural Decoding of fMRI with Domain Adaptation -- Automatic Couinaud Segmentation from CT Volumes on Liver Using GLC-Unet -- Biomedical Image Segmentation by Retina-like Sequential Attention Mechanism Using Only A Few Training Images -- Conv-MCD: A Plug-and-Play Multi-task Module for Medical Image Segmentation -- Detecting abnormalities in resting-state dynamics: An unsupervised learning approach -- Distanced LSTM: Time-Distanced Gates in Long Short-Term Memory Models for Lung Cancer Detection -- Dense-residual Attention Network for Skin Lesion Segmentation -- Confounder-Aware Visualization of ConvNets -- Detecting Lesion Bounding Ellipses With Gaussian Proposal Networks -- Modelling Airway Geometry as Stock Market Data using Bayesian Changepoint Detection -- Unsupervised Lesion Detection with Locally Gaussian Approximation -- A Hybrid Multi-atrous and Multi-scale Network for Liver Lesion Detection -- BOLD fMRI-based Brain Perfusion Prediction Using Deep Dilated Wide Activation Networks -- Jointly Discriminative and Generative Recurrent Neural Networks for Learning from fMRI -- Unsupervised Conditional Consensus Adversarial Network for Brain Disease Identification with Structural MRI -- A Maximum Entropy Deep Reinforcement Learning Neural Tracker -- Weakly Supervised Confidence Learning for Brain MR Image Dense Parcellation -- Select, Attend, and Transfer: Light, Learnable Skip Connections -- Learning-based Bone Quality Classification Method for Spinal Metastasis -- Automated Segmentation of Skin Lesion Based on Pyramid Attention Network -- Relu cascade of feature pyramid networks for CT pulmonary nodule detection -- Joint Localization of Optic Disc and Fovea in Ultra-Widefield Fundus Images -- Multi-Scale Attentional Network for Multi-Focal Segmentation of Active Bleed after Pelvic Fractures -- Lesion Detection by Efficiently Bridging 3D Context -- Communal Domain Learning for Registration in Drifted Image Spaces -- Conv2Warp: An unsupervised deformable image registration with continuous convolution and warping -- Semantic filtering through deep source separation on microscopy images -- Adaptive Functional Connectivity Network using Parallel Hierarchical BiLSTM for MCI Diagnosis -- Multi-Template based Auto-weighted Adaptive Structural Learning for ASD Diagnosis -- Learn to Step-wise Focus on Targets for Biomedical Image Segmentation -- Renal Cell Carcinoma Staging with Learnable Image Histogram-based Deep Neural Network -- Weakly Supervised Learning Strategy for Lung Defect Segmentation -- Gated Recurrent Neural Networks for Accelerated Ventilation MRI -- A Cascaded Multi-Modality Analysis in Mild Cognitive Impairment -- Deep Residual Learning for Instrument Segmentation in Robotic Surgery -- Deep learning model integrating dilated convolution and deep supervision for brain tumor segmentation in multi-parametric MRI -- A joint 3D UNet-Graph Neural Network-based method for Airway Segmentation from chest CTs -- Automatic Fetal Brain Extraction Using Multi-Stage U-Net with Deep Supervision -- Cross-Modal Attention-Guided Convolutional Network for Multi-Modal Cardiac Segmentation -- High- and Low-Level Feature Enhancement for Medical Image Segmentation -- Shape-Aware Complementary-Task Learning for Multi-Organ Segmentation -- An Active Learning Approach for Reducing Annotation Cost in Skin Lesion Analysis -- Tree-LSTM: Using LSTM to Encode Memory in Anatomical Tree Prediction from 3D Images -- FAIM-A ConvNet Method for Unsupervised 3D Medical Image Registration -- Functional data and long short-term memory networks for diagnosis of Parkinson's Disease -- Joint Holographic Detection and Reconstruction -- Reinforced Transformer for Medical Image Captioning -- Multi Task Convolutional Neural Network for Joint Bone Age Assessment and Ossification Center Detection from Hand Radiograph. |
| Record Nr. | UNISA-996466192503316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Machine Learning in Medical Imaging : 10th International Workshop, MLMI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings / / edited by Heung-Il Suk, Mingxia Liu, Pingkun Yan, Chunfeng Lian
| Machine Learning in Medical Imaging : 10th International Workshop, MLMI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings / / edited by Heung-Il Suk, Mingxia Liu, Pingkun Yan, Chunfeng Lian |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XVIII, 695 p. 310 illus., 245 illus. in color.) |
| Disciplina |
616.07540285
006.6 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Artificial intelligence Image Processing and Computer Vision Artificial Intelligence |
| ISBN | 3-030-32692-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | rain MR Image Segmentation in Small Dataset with Adversarial Defense and Task Reorganization -- Spatial Regularized Classification Network for Spinal Dislocation Diagnosis -- Globally-Aware Multiple Instance Classifier for Breast Cancer Screening -- Advancing Pancreas Segmentation in Multi-protocol MRI Volumes using Hausdorff-Sine Loss Function -- WSI-Net: Branch-based and Hierarchy-aware Network for Segmentation and Classification of Breast Histopathological Whole-slide Images -- Lesion Detection with Deep Aggregated 3D Contextual Feature and Auxiliary Information -- MSAFusionNet: Multiple Subspace Attention Based Deep Multi-modal Fusion Network -- DCCL: A Benchmark for Cervical Cytology Analysis -- Smartphone-Supported Malaria Diagnosis Based on Deep Learning -- Children's Neuroblastoma Segmentation using Morphological Features -- GFD Faster R-CNN: Gabor Fractal DenseNet Faster R-CNN for automatic detection of esophageal abnormalities in endoscopic images -- Deep Active Lesion Segmentation -- Infant Brain Deformable Registration Using Global and Local Label-Driven Deep Regression Learning -- A Relation Hashing Network Embedded with Prior Features for Skin Lesion Classification -- End-to-End Adversarial Shape Learning for Abdomen Organ Deep Segmentation -- Privacy-preserving Federated Brain Tumour Segmentation -- Residual Attention Generative Adversarial Networks for Nuclei Detection on Routine Colon Cancer Histology Images -- Semi-Supervised Multi-Task Learning With Chest X-Ray Images -- Novel Bi-directional Images Synthesis based on WGAN-GP with GMM-based Noise Generation -- Pseudo-labeled bootstrapping and multi-stage transfer learning for the classification and localization of dysplasia in Barrett’s Esophagus -- Anatomy-Aware Self-supervised Fetal MRI Synthesis from Unpaired Ultrasound Images -- Boundary Aware Networks for Medical Image Segmentation -- Automatic Rodent Brain MRI Lesion Segmentation with Fully Convolutional Networks -- Morphological Simplification of Brain MR Images by Deep Learning for Facilitating Deformable Registration -- Joint Shape Representation and Classification for Detecting PDAC -- FusionNet: Incorporating Shape and Texture for Abnormality Detection in 3D Abdominal CT Scans -- Weakly supervised segmentation by a deep geodesic prior -- Ultrasound Liver Fibrosis Diagnosis using Multi-indicator guided Deep Neural Networks -- Correspondence-Steered Volumetric Descriptor Learning Using Deep Functional Maps -- Sturm: Sparse Tubal-Regularized Multilinear Regression for fMRI -- Improving Whole-Brain Neural Decoding of fMRI with Domain Adaptation -- Automatic Couinaud Segmentation from CT Volumes on Liver Using GLC-Unet -- Biomedical Image Segmentation by Retina-like Sequential Attention Mechanism Using Only A Few Training Images -- Conv-MCD: A Plug-and-Play Multi-task Module for Medical Image Segmentation -- Detecting abnormalities in resting-state dynamics: An unsupervised learning approach -- Distanced LSTM: Time-Distanced Gates in Long Short-Term Memory Models for Lung Cancer Detection -- Dense-residual Attention Network for Skin Lesion Segmentation -- Confounder-Aware Visualization of ConvNets -- Detecting Lesion Bounding Ellipses With Gaussian Proposal Networks -- Modelling Airway Geometry as Stock Market Data using Bayesian Changepoint Detection -- Unsupervised Lesion Detection with Locally Gaussian Approximation -- A Hybrid Multi-atrous and Multi-scale Network for Liver Lesion Detection -- BOLD fMRI-based Brain Perfusion Prediction Using Deep Dilated Wide Activation Networks -- Jointly Discriminative and Generative Recurrent Neural Networks for Learning from fMRI -- Unsupervised Conditional Consensus Adversarial Network for Brain Disease Identification with Structural MRI -- A Maximum Entropy Deep Reinforcement Learning Neural Tracker -- Weakly Supervised Confidence Learning for Brain MR Image Dense Parcellation -- Select, Attend, and Transfer: Light, Learnable Skip Connections -- Learning-based Bone Quality Classification Method for Spinal Metastasis -- Automated Segmentation of Skin Lesion Based on Pyramid Attention Network -- Relu cascade of feature pyramid networks for CT pulmonary nodule detection -- Joint Localization of Optic Disc and Fovea in Ultra-Widefield Fundus Images -- Multi-Scale Attentional Network for Multi-Focal Segmentation of Active Bleed after Pelvic Fractures -- Lesion Detection by Efficiently Bridging 3D Context -- Communal Domain Learning for Registration in Drifted Image Spaces -- Conv2Warp: An unsupervised deformable image registration with continuous convolution and warping -- Semantic filtering through deep source separation on microscopy images -- Adaptive Functional Connectivity Network using Parallel Hierarchical BiLSTM for MCI Diagnosis -- Multi-Template based Auto-weighted Adaptive Structural Learning for ASD Diagnosis -- Learn to Step-wise Focus on Targets for Biomedical Image Segmentation -- Renal Cell Carcinoma Staging with Learnable Image Histogram-based Deep Neural Network -- Weakly Supervised Learning Strategy for Lung Defect Segmentation -- Gated Recurrent Neural Networks for Accelerated Ventilation MRI -- A Cascaded Multi-Modality Analysis in Mild Cognitive Impairment -- Deep Residual Learning for Instrument Segmentation in Robotic Surgery -- Deep learning model integrating dilated convolution and deep supervision for brain tumor segmentation in multi-parametric MRI -- A joint 3D UNet-Graph Neural Network-based method for Airway Segmentation from chest CTs -- Automatic Fetal Brain Extraction Using Multi-Stage U-Net with Deep Supervision -- Cross-Modal Attention-Guided Convolutional Network for Multi-Modal Cardiac Segmentation -- High- and Low-Level Feature Enhancement for Medical Image Segmentation -- Shape-Aware Complementary-Task Learning for Multi-Organ Segmentation -- An Active Learning Approach for Reducing Annotation Cost in Skin Lesion Analysis -- Tree-LSTM: Using LSTM to Encode Memory in Anatomical Tree Prediction from 3D Images -- FAIM-A ConvNet Method for Unsupervised 3D Medical Image Registration -- Functional data and long short-term memory networks for diagnosis of Parkinson's Disease -- Joint Holographic Detection and Reconstruction -- Reinforced Transformer for Medical Image Captioning -- Multi Task Convolutional Neural Network for Joint Bone Age Assessment and Ossification Center Detection from Hand Radiograph. |
| Record Nr. | UNINA-9910349274203321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Machine Learning in Medical Imaging [[electronic resource] ] : 9th International Workshop, MLMI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings / / edited by Yinghuan Shi, Heung-Il Suk, Mingxia Liu
| Machine Learning in Medical Imaging [[electronic resource] ] : 9th International Workshop, MLMI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings / / edited by Yinghuan Shi, Heung-Il Suk, Mingxia Liu |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (XIII, 409 p. 152 illus.) |
| Disciplina | 006.37 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Artificial intelligence Health informatics Data mining Image Processing and Computer Vision Artificial Intelligence Health Informatics Data Mining and Knowledge Discovery |
| ISBN | 3-030-00919-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996466333803316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Machine Learning in Medical Imaging : 9th International Workshop, MLMI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings / / edited by Yinghuan Shi, Heung-Il Suk, Mingxia Liu
| Machine Learning in Medical Imaging : 9th International Workshop, MLMI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings / / edited by Yinghuan Shi, Heung-Il Suk, Mingxia Liu |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (XIII, 409 p. 152 illus.) |
| Disciplina |
006.37
006.6 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Artificial intelligence Health informatics Data mining Image Processing and Computer Vision Artificial Intelligence Health Informatics Data Mining and Knowledge Discovery |
| ISBN | 3-030-00919-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910349403703321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||