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Deep learning for medical image analysis / / edited by Kevin Zhou, Hayit Greenspan, Dinggang Shen
| Deep learning for medical image analysis / / edited by Kevin Zhou, Hayit Greenspan, Dinggang Shen |
| Autore | Zhou S. |
| Edizione | [First edition.] |
| Pubbl/distr/stampa | London, England : , : Academic Press, , 2017 |
| Descrizione fisica | 1 online resource (460 pages) : illustrations, photographs |
| Disciplina | 616.07540285 |
| Soggetto topico |
Diagnostic imaging - Data processing
Image analysis |
| ISBN |
0-12-810409-0
0-12-810408-2 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- Medical Image Detection and recognition -- Medical image segmentation -- Medical image registration -- Computer-aided diagnosis and disease quantification -- Others. |
| Record Nr. | UNINA-9910162740003321 |
Zhou S.
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| London, England : , : Academic Press, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Information Processing in Medical Imaging [[electronic resource] ] : 25th International Conference, IPMI 2017, Boone, NC, USA, June 25-30, 2017, Proceedings / / edited by Marc Niethammer, Martin Styner, Stephen Aylward, Hongtu Zhu, Ipek Oguz, Pew-Thian Yap, Dinggang Shen
| Information Processing in Medical Imaging [[electronic resource] ] : 25th International Conference, IPMI 2017, Boone, NC, USA, June 25-30, 2017, Proceedings / / edited by Marc Niethammer, Martin Styner, Stephen Aylward, Hongtu Zhu, Ipek Oguz, Pew-Thian Yap, Dinggang Shen |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (XVI, 687 p. 285 illus.) |
| Disciplina | 616.0754 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Pattern recognition Health informatics Radiology Artificial intelligence Mathematical statistics Image Processing and Computer Vision Pattern Recognition Health Informatics Imaging / Radiology Artificial Intelligence Probability and Statistics in Computer Science |
| ISBN | 3-319-59050-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Analysis on manifolds -- Shape analysis -- Disease diagnosis/progression -- Brain networks an connectivity -- Diffusion imaging -- Quantitative imaging -- Imaging genomics -- Image registration -- Segmentation -- General image analysis. <. |
| Record Nr. | UNISA-996466205003316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Information Processing in Medical Imaging : 25th International Conference, IPMI 2017, Boone, NC, USA, June 25-30, 2017, Proceedings / / edited by Marc Niethammer, Martin Styner, Stephen Aylward, Hongtu Zhu, Ipek Oguz, Pew-Thian Yap, Dinggang Shen
| Information Processing in Medical Imaging : 25th International Conference, IPMI 2017, Boone, NC, USA, June 25-30, 2017, Proceedings / / edited by Marc Niethammer, Martin Styner, Stephen Aylward, Hongtu Zhu, Ipek Oguz, Pew-Thian Yap, Dinggang Shen |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (XVI, 687 p. 285 illus.) |
| Disciplina | 616.0754 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Computer vision
Pattern recognition systems Medical informatics Radiology Artificial intelligence Computer science - Mathematics Mathematical statistics Computer Vision Automated Pattern Recognition Health Informatics Artificial Intelligence Probability and Statistics in Computer Science |
| ISBN | 3-319-59050-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Analysis on manifolds -- Shape analysis -- Disease diagnosis/progression -- Brain networks an connectivity -- Diffusion imaging -- Quantitative imaging -- Imaging genomics -- Image registration -- Segmentation -- General image analysis. <. |
| Record Nr. | UNINA-9910484399503321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Machine Learning in Dentistry / / edited by Ching-Chang Ko, Dinggang Shen, Li Wang
| Machine Learning in Dentistry / / edited by Ching-Chang Ko, Dinggang Shen, Li Wang |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 |
| Descrizione fisica | 1 online resource (186 pages) |
| Disciplina | 006.31 |
| Collana | Management and industrial engineering |
| Soggetto topico |
Dentistry
Big data Big Data |
| ISBN | 3-030-71881-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Machine Learning for Dental Imaging: Machine Learning for CBCT Segmentation of Craniofacial 3D Image -- Machine Learning for Automatic Landmark Detection of 3D Imaging -- Machine Learning for Generating Dental CT from Magnetic Resonance Imaging (MRI) -- Machine Learning for 2D Dynamic Facial Photographs. Machine Learning for Oral Diagnosis and Treatment: Machine Learning for Orthodontic Diagnosis and Treatment Planning -- Machine Learning for Diagnosis of Periodontal Diseases -- Machine Learning for Oral Microbiome -- Machine Learning for Characterization of Craniofacial Anomaly -- Machine Learning for Orthognathic Surgery -- Machine Learning for Bone Tissue Engineering. Machine Learning and Dental Designs: Machine Learning for Orthodontic CAD/CAM Technologies -- Machine Learning for Design of Dental Implants -- Machine Learning for Optimization of Dental Material Processing. Machine Learning Supporting Dental Research: Machine Learningfor Data Mining in Teledentistry -- Machine Learning for Evidence-Based Literature Search -- Machine Learning in Genetics and Genomics -- Machine Learning and Finite Element Modeling. |
| Record Nr. | UNINA-9910495242003321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Machine Learning in Medical Imaging [[electronic resource] ] : 4th International Workshop, MLMI 2013, Held in Conjunction with MICCAI 2013, Nagoya, Japan, September 22, 2013, Proceedings / / edited by Guorong Wu, Daoqiang Zhang, Dinggang Shen, Pingkun Yan, Kenji Suzuki, Fei Wang
| Machine Learning in Medical Imaging [[electronic resource] ] : 4th International Workshop, MLMI 2013, Held in Conjunction with MICCAI 2013, Nagoya, Japan, September 22, 2013, Proceedings / / edited by Guorong Wu, Daoqiang Zhang, Dinggang Shen, Pingkun Yan, Kenji Suzuki, Fei Wang |
| Edizione | [1st ed. 2013.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2013 |
| Descrizione fisica | 1 online resource (XII, 262 p. 94 illus.) |
| Disciplina |
006.6
006.37 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Pattern recognition Artificial intelligence Database management Computer graphics Image Processing and Computer Vision Pattern Recognition Artificial Intelligence Computer Imaging, Vision, Pattern Recognition and Graphics Database Management Computer Graphics |
| ISBN | 3-319-02267-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Unsupervised Deep Learning for Hippocampus Segmentation in 7.0 Tesla MR Images -- Integrating Multiple Network Properties for MCI Identification -- Learning-Boosted Label Fusion for Multi-atlas Auto-Segmentation -- Volumetric Segmentation of Key Fetal Brain Structures in 3D Ultrasound -- Sparse Classification with MRI Based Markers for Neuromuscular Disease Categorization -- Fully Automatic Detection of the Carotid Artery from Volumetric Ultrasound Images Using Anatomical Position-Dependent LBP Features -- A Transfer-Learning Approach to Image Segmentation Across Scanners by Maximizing Distribution Similarity -- A New Algorithm of Electronic Cleansing for Weak Faecal-Tagging CT Colonography -- A Unified Approach to Shape Model Fitting and Non-rigid Registration -- A Bayesian Algorithm for Image-Based Time-to-Event Prediction -- Patient-Specific Manifold Embedding of Multispectral Images Using Kernel Combinations -- fMRI Analysis with Sparse Weisfeiler-Lehman Graph Statistics -- Patch-Based Segmentation without Registration: Application to Knee MRI -- Flow-Based Correspondence Matching in Stereovision -- Thickness NETwork (ThickNet) Features for the Detection of Prodromal AD -- Metric Space Structures for Computational Anatomy -- Discriminative Group Sparse Representation for Mild Cognitive Impairment Classification -- Temporally Dynamic Resting-State Functional Connectivity Networks for Early MCI Identification -- An Improved Optimization Method for the Relevance Voxel Machine -- Disentanglement of Session and Plasticity Effects in Longitudinal fMRI Studies -- Identification of Alzheimer’s Disease Using Incomplete Multimodal Dataset via Matrix Shrinkage and Completion -- On Feature Relevance in Image-Based Prediction Models: An Empirical Study -- Decision Forests with Spatio-Temporal Features for Graph-Based Tumor Segmentation in 4D Lung CT -- Improving Probabilistic Image Registration via Reinforcement Learning and Uncertainty Evaluation -- HEp-2 Cell Image Classification: A Comparative Analysis -- A 2.5D Colon Wall Flattening Model for CT-Based Virtual Colonoscopy -- Augmenting Auto-context with Global Geometric Features for Spinal Cord Segmentation -- Large-Scale Manifold Learning Using an Adaptive Sparse Neighbor Selection Approach for Brain Tumor Progression Prediction -- Ensemble Universum SVM Learning for Multimodal Classification of Alzheimer’s Disease -- Joint Sparse Coding Spatial Pyramid Matching for Classification of Color Blood Cell Image -- Multi-task Sparse Classifier for Diagnosis of MCI Conversion to AD with Longitudinal MR Images -- Sparse Multimodal Manifold-Regularized Transfer Learning for MCI Conversion Prediction. |
| Record Nr. | UNISA-996466031503316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Machine Learning in Medical Imaging : 4th International Workshop, MLMI 2013, Held in Conjunction with MICCAI 2013, Nagoya, Japan, September 22, 2013, Proceedings / / edited by Guorong Wu, Daoqiang Zhang, Dinggang Shen, Pingkun Yan, Kenji Suzuki, Fei Wang
| Machine Learning in Medical Imaging : 4th International Workshop, MLMI 2013, Held in Conjunction with MICCAI 2013, Nagoya, Japan, September 22, 2013, Proceedings / / edited by Guorong Wu, Daoqiang Zhang, Dinggang Shen, Pingkun Yan, Kenji Suzuki, Fei Wang |
| Edizione | [1st ed. 2013.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2013 |
| Descrizione fisica | 1 online resource (XII, 262 p. 94 illus.) |
| Disciplina |
006.6
006.37 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Computer vision
Pattern recognition systems Artificial intelligence Image processing - Digital techniques Database management Computer graphics Computer Vision Automated Pattern Recognition Artificial Intelligence Computer Imaging, Vision, Pattern Recognition and Graphics Database Management Computer Graphics |
| ISBN | 3-319-02267-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Unsupervised Deep Learning for Hippocampus Segmentation in 7.0 Tesla MR Images -- Integrating Multiple Network Properties for MCI Identification -- Learning-Boosted Label Fusion for Multi-atlas Auto-Segmentation -- Volumetric Segmentation of Key Fetal Brain Structures in 3D Ultrasound -- Sparse Classification with MRI Based Markers for Neuromuscular Disease Categorization -- Fully Automatic Detection of the Carotid Artery from Volumetric Ultrasound Images Using Anatomical Position-Dependent LBP Features -- A Transfer-Learning Approach to Image Segmentation Across Scanners by Maximizing Distribution Similarity -- A New Algorithm of Electronic Cleansing for Weak Faecal-Tagging CT Colonography -- A Unified Approach to Shape Model Fitting and Non-rigid Registration -- A Bayesian Algorithm for Image-Based Time-to-Event Prediction -- Patient-Specific Manifold Embedding of Multispectral Images Using Kernel Combinations -- fMRI Analysis with Sparse Weisfeiler-Lehman Graph Statistics -- Patch-Based Segmentation without Registration: Application to Knee MRI -- Flow-Based Correspondence Matching in Stereovision -- Thickness NETwork (ThickNet) Features for the Detection of Prodromal AD -- Metric Space Structures for Computational Anatomy -- Discriminative Group Sparse Representation for Mild Cognitive Impairment Classification -- Temporally Dynamic Resting-State Functional Connectivity Networks for Early MCI Identification -- An Improved Optimization Method for the Relevance Voxel Machine -- Disentanglement of Session and Plasticity Effects in Longitudinal fMRI Studies -- Identification of Alzheimer’s Disease Using Incomplete Multimodal Dataset via Matrix Shrinkage and Completion -- On Feature Relevance in Image-Based Prediction Models: An Empirical Study -- Decision Forests with Spatio-Temporal Features for Graph-Based Tumor Segmentation in 4D Lung CT -- Improving Probabilistic Image Registration via Reinforcement Learning and Uncertainty Evaluation -- HEp-2 Cell Image Classification: AComparative Analysis -- A 2.5D Colon Wall Flattening Model for CT-Based Virtual Colonoscopy -- Augmenting Auto-context with Global Geometric Features for Spinal Cord Segmentation -- Large-Scale Manifold Learning Using an Adaptive Sparse Neighbor Selection Approach for Brain Tumor Progression Prediction -- Ensemble Universum SVM Learning for Multimodal Classification of Alzheimer’s Disease -- Joint Sparse Coding Spatial Pyramid Matching for Classification of Color Blood Cell Image -- Multi-task Sparse Classifier for Diagnosis of MCI Conversion to AD with Longitudinal MR Images -- Sparse Multimodal Manifold-Regularized Transfer Learning for MCI Conversion Prediction. |
| Record Nr. | UNINA-9910482954003321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Machine Learning in Medical Imaging [[electronic resource] ] : Third International Workshop, MLMI 2012, Held in Conjunction with MICCAI 2012, Nice, France, October 1, 2012, Revised Selected Papers / / edited by Fei Wang, Dinggang Shen, Pingkun Yan, Kenji Suzuki
| Machine Learning in Medical Imaging [[electronic resource] ] : Third International Workshop, MLMI 2012, Held in Conjunction with MICCAI 2012, Nice, France, October 1, 2012, Revised Selected Papers / / edited by Fei Wang, Dinggang Shen, Pingkun Yan, Kenji Suzuki |
| Edizione | [1st ed. 2012.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2012 |
| Descrizione fisica | 1 online resource (XII, 276 p. 91 illus.) |
| Disciplina | 616.0754 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Pattern recognition Artificial intelligence Database management Computer graphics Image Processing and Computer Vision Pattern Recognition Artificial Intelligence Computer Imaging, Vision, Pattern Recognition and Graphics Database Management Computer Graphics |
| Soggetto non controllato |
MLMI
MICCAI Medical imaging |
| ISBN | 3-642-35428-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996465948303316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2012 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Machine Learning in Medical Imaging [[electronic resource] ] : Second International Workshop, MLMI 2011, Held in Conjunction with MICCAI 2011, Toronto, Canada, September 18, 2011, Proceedings / / edited by Kenji Suzuki, Fei Wang, Dinggang Shen, Pingkun Yan
| Machine Learning in Medical Imaging [[electronic resource] ] : Second International Workshop, MLMI 2011, Held in Conjunction with MICCAI 2011, Toronto, Canada, September 18, 2011, Proceedings / / edited by Kenji Suzuki, Fei Wang, Dinggang Shen, Pingkun Yan |
| Edizione | [1st ed. 2011.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2011 |
| Descrizione fisica | 1 online resource (XIII, 371 p.) |
| Disciplina | 610.285/63 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Optical data processing
Pattern recognition Artificial intelligence Algorithms Application software Image Processing and Computer Vision Pattern Recognition Computer Imaging, Vision, Pattern Recognition and Graphics Artificial Intelligence Algorithm Analysis and Problem Complexity Information Systems Applications (incl. Internet) |
| ISBN | 3-642-24319-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996465398303316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2011 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Machine Learning in Medical Imaging [[electronic resource] ] : First International Workshop, MLMI 2010, Held in Conjunction with MICCAI 2010, Beijing, China, September 20, 2010, Proceedings / / edited by Fei Wang, Pingkun Yan, Kenji Suzuki, Dinggang Shen
| Machine Learning in Medical Imaging [[electronic resource] ] : First International Workshop, MLMI 2010, Held in Conjunction with MICCAI 2010, Beijing, China, September 20, 2010, Proceedings / / edited by Fei Wang, Pingkun Yan, Kenji Suzuki, Dinggang Shen |
| Edizione | [1st ed. 2010.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2010 |
| Descrizione fisica | 1 online resource (IX, 192 p. 84 illus.) |
| Disciplina | 616.07/54 |
| Collana | Image Processing, Computer Vision, Pattern Recognition, and Graphics |
| Soggetto topico |
Artificial intelligence
Optical data processing Radiology Pattern recognition Algorithms Artificial Intelligence Image Processing and Computer Vision Imaging / Radiology Pattern Recognition Computer Imaging, Vision, Pattern Recognition and Graphics Algorithm Analysis and Problem Complexity |
| Soggetto genere / forma | Kongress. |
| ISBN |
1-280-38927-3
9786613567192 3-642-15948-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Fast Automatic Detection of Calcified Coronary Lesions in 3D Cardiac CT Images -- Automated Intervertebral Disc Detection from Low Resolution, Sparse MRI Images for the Planning of Scan Geometries -- Content-Based Medical Image Retrieval with Metric Learning via Rank Correlation -- A Hyper-parameter Inference for Radon Transformed Image Reconstruction Using Bayesian Inference -- Patch-Based Generative Shape Model and MDL Model Selection for Statistical Analysis of Archipelagos -- Prediction of Dementia by Hippocampal Shape Analysis -- Multi-Class Sparse Bayesian Regression for Neuroimaging Data Analysis -- Appearance Normalization of Histology Slides -- Parallel Mean Shift for Interactive Volume Segmentation -- Soft Tissue Discrimination Using Magnetic Resonance Elastography with a New Elastic Level Set Model -- Fast and Automatic Heart Isolation in 3D CT Volumes: Optimal Shape Initialization -- Relation-Aware Spreadsheets for Multimodal Volume Segmentation and Visualization -- A Bayesian Learning Application to Automated Tumour Segmentation for Tissue Microarray Analysis -- Generalized Sparse Classifiers for Decoding Cognitive States in fMRI -- Manifold Learning for Biomarker Discovery in MR Imaging -- Optimal Live Cell Tracking for Cell Cycle Study Using Time-Lapse Fluorescent Microscopy Images -- Fully Automatic Joint Segmentation for Computer-Aided Diagnosis and Planning -- Accurate Identification of MCI Patients via Enriched White-Matter Connectivity Network -- Feature Extraction for fMRI-Based Human Brain Activity Recognition -- Sparse Spatio-temporal Inference of Electromagnetic Brain Sources -- Optimal Gaussian Mixture Models of Tissue Intensities in Brain MRI of Patients with Multiple-Sclerosis -- Preliminary Study on Appearance-Based Detection of Anatomical Point Landmarks in Body Trunk CT Images -- Principal-Component Massive-Training Machine-Learning Regression for False-Positive Reduction in Computer-Aided Detection of Polyps in CT Colonography. |
| Record Nr. | UNISA-996465876403316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2010 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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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 | ||
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