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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
Opac: Controlla la disponibilità qui
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 Computer vision
Artificial intelligence
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 MemoryModels 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
Opac: Controlla la disponibilità qui
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
Opac: Controlla la disponibilità qui
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
Opac: Controlla la disponibilità qui
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
Opac: Controlla la disponibilità qui
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
Opac: Controlla la disponibilità qui
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
Opac: Controlla la disponibilità qui
Prostate Cancer Imaging: Computer-Aided Diagnosis, Prognosis, and Intervention [[electronic resource] ] : International Workshop, Held in Conjunction with MICCAI 2010, Beijing, China, September 24, 2010, Proceedings / / edited by Anant Madabhushi, Jason Dowling, Pingkun Yan, Aaron Fenster, Purang Abolmaesumi, Nobuhiko Hata
Prostate Cancer Imaging: Computer-Aided Diagnosis, Prognosis, and Intervention [[electronic resource] ] : International Workshop, Held in Conjunction with MICCAI 2010, Beijing, China, September 24, 2010, Proceedings / / edited by Anant Madabhushi, Jason Dowling, Pingkun Yan, Aaron Fenster, Purang Abolmaesumi, Nobuhiko Hata
Edizione [1st ed. 2010.]
Pubbl/distr/stampa Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2010
Descrizione fisica 1 online resource (X, 146 p. 67 illus.)
Disciplina 005.437
4.019
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico User interfaces (Computer systems)
Optical data processing
Pattern recognition
Computer graphics
Computer simulation
User Interfaces and Human Computer Interaction
Image Processing and Computer Vision
Pattern Recognition
Computer Graphics
Computer Imaging, Vision, Pattern Recognition and Graphics
Simulation and Modeling
Soggetto genere / forma Kongress
ISBN 1-280-38932-X
9786613567246
3-642-15989-3
Classificazione 610
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Prostate Cancer MR Imaging -- Computer Aided Detection of Prostate Cancer Using T2, DWI and DCE MRI: Methods and Clinical Applications -- Prostate Cancer Segmentation Using Multispectral Random Walks -- Automatic MRI Atlas-Based External Beam Radiation Therapy Treatment Planning for Prostate Cancer -- An Efficient Inverse-Consistent Diffeomorphic Image Registration Method for Prostate Adaptive Radiotherapy -- Atlas Based Segmentation and Mapping of Organs at Risk from Planning CT for the Development of Voxel-Wise Predictive Models of Toxicity in Prostate Radiotherapy -- Realtime TRUS/MRI Fusion Targeted-Biopsy for Prostate Cancer: A Clinical Demonstration of Increased Positive Biopsy Rates -- HistoCAD: Machine Facilitated Quantitative Histoimaging with Computer Assisted Diagnosis -- Registration of In Vivo Prostate Magnetic Resonance Images to Digital Histopathology Images -- High-Throughput Prostate Cancer Gland Detection, Segmentation, and Classification from Digitized Needle Core Biopsies -- Automated Analysis of PIN-4 Stained Prostate Needle Biopsies -- Augmented Reality Image Guidance in Minimally Invasive Prostatectomy -- Texture Guided Active Appearance Model Propagation for Prostate Segmentation -- Novel Stochastic Framework for Accurate Segmentation of Prostate in Dynamic Contrast Enhanced MRI -- Boundary Delineation in Prostate Imaging Using Active Contour Segmentation Method with Interactively Defined Object Regions.
Record Nr. UNISA-996466246303316
Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2010
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui