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Biblioteca

MARC Lista (tabellare)
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries [[electronic resource] ] : Third International Workshop, BrainLes 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 14, 2017, Revised Selected Papers / / edited by Alessandro Crimi, Spyridon Bakas, Hugo Kuijf, Bjoern Menze, Mauricio Reyes
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries [[electronic resource] ] : Third International Workshop, BrainLes 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 14, 2017, Revised Selected Papers / / edited by Alessandro Crimi, Spyridon Bakas, Hugo Kuijf, Bjoern Menze, Mauricio Reyes
Edizione [1st ed. 2018.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018
Descrizione fisica 1 online resource (XIII, 517 p. 233 illus.)
Disciplina 616.8
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Optical data processing
Artificial intelligence
Mathematical statistics
Health informatics
Image Processing and Computer Vision
Artificial Intelligence
Probability and Statistics in Computer Science
Health Informatics
ISBN 3-319-75238-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Invited Talks -- Dice overlap measures for objects of unknown number: Application to lesion segmentation -- Lesion Detection, Segmentation and Prediction in Multiple Sclerosis Clinical Trials -- Brain Lesion Image Analysis -- Automated Segmentation of Multiple Sclerosis Lesions using Multi-Dimensional Gated Recurrent Units -- Joint Intensity Fusion Image Synthesis Applied to Multiple Sclerosis Lesion Segmentation -- MARCEL (inter-Modality Ane Registration with CorELation ratio): An Application for Brain Shift Correction in Ultrasound-Guided Brain Tumor Resection -- Generalised Wasserstein Dice Score for Imbalanced Multi-class Segmentation using Holistic Convolutional Networks -- Overall Survival Time Prediction for High Grade Gliomas based on Sparse Representation Framework -- Traumatic Brain Lesion Quantication based on Mean Diusivity Changes -- Pairwise, Ordinal Outlier Detection of Traumatic Brain Injuries -- Sub-Acute & Chronic Ischemic Stroke Lesion MRI Segmentation -- Brain Tumor Segmentation Using an Adversarial Network -- Brain Cancer Imaging Phenomics Toolkit (brain-CaPTk): An Interactive Platform for Quantitative Analysis of Glioblastoma -- Brain Tumor Image Segmentation -- Deep Learning based Multimodal Brain Tumor Diagnosis -- Multimodal Brain Tumor Segmentation using Ensemble of Forest Method -- Pooling-free fully convolutional networks with dense skip connections for semantic segmentation, with application to brain tumor segmentation -- Automatic Brain Tumor Segmentation using Cascaded Anisotropic Convolutional Neural Networks -- 3D Brain Tumor Segmentation through Integrating Multiple 2D FCNNs -- MRI Brain Tumor Segmentation and Patient Survival Prediction using Random Forests and Fully Convolutional Networks -- Automatic Segmentation and Overall Survival Prediction in Gliomas using Fully Convolutional Neural Network and Texture Analysis -- Multimodal Brain Tumor Segmentation Using 3D Convolutional Networks -- A Conditional Adversarial Network for Semantic Segmentation of Brain Tumor -- Dilated Convolutions for Brain Tumor Segmentation in MRI Scans -- Residual Encoder and Convolutional Decoder Neural Network for Glioma Segmentation -- TPCNN: Two-phase Patch-based Convolutional Neural Network for Automatic Brain Tumor Segmentation and Survival Prediction -- Brain Tumor Segmentation and Radiomics Survival Prediction: Contribution to the BRATS 2017 Challenge -- Multi-modal PixelNet for Brain Tumor Segmentation -- Brain Tumor Segmentation using Dense Fully Convolutional Neural Network -- Brain Tumor Segmentation in MRI Scans using Deeply-Supervised Neural Networks -- Brain Tumor Segmentation and Parsing on MRIs using Multiresolution Neural Networks -- Brain Tumor Segmentation using Deep Fully Convolutional Neural Networks -- Glioblastoma and Survival Prediction -- MRI Augmentation via Elastic Registration for Brain Lesions Segmentation -- Cascaded V-Net using ROI masks for brain tumor segmentation -- Brain Tumor Segmentation using a 3D FCN with Multi-Scale Loss -- Brain tumor segmentation using a multi-path CNN based method -- 3D Deep Neural Network-Based Brain Tumor Segmentation Using Multimodality Magnetic Resonance Sequences -- Automated Brain Tumor Segmentation on Magnetic Resonance Images (MRIs) and Patient Overall Survival Prediction using Support Vector Machines -- Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation -- Tumor segmentation from multimodal MRI using random forest with superpixel and tensor based feature extraction -- Towards Uncertainty-assisted Brain Tumor Segmentation and Survival Prediction -- Ischemic Stroke Lesion Image Segmentation -- WMH Segmentation Challenge: a Texture-based Classication Approach -- White Matter Hyperintensities Segmentation In a Few Seconds Using Fully Convolutional Network and Transfer Learning.
Record Nr. UNINA-9910349460103321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries [[electronic resource] ] : Third International Workshop, BrainLes 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 14, 2017, Revised Selected Papers / / edited by Alessandro Crimi, Spyridon Bakas, Hugo Kuijf, Bjoern Menze, Mauricio Reyes
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries [[electronic resource] ] : Third International Workshop, BrainLes 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 14, 2017, Revised Selected Papers / / edited by Alessandro Crimi, Spyridon Bakas, Hugo Kuijf, Bjoern Menze, Mauricio Reyes
Edizione [1st ed. 2018.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018
Descrizione fisica 1 online resource (XIII, 517 p. 233 illus.)
Disciplina 616.8
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Optical data processing
Artificial intelligence
Mathematical statistics
Health informatics
Image Processing and Computer Vision
Artificial Intelligence
Probability and Statistics in Computer Science
Health Informatics
ISBN 3-319-75238-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Invited Talks -- Dice overlap measures for objects of unknown number: Application to lesion segmentation -- Lesion Detection, Segmentation and Prediction in Multiple Sclerosis Clinical Trials -- Brain Lesion Image Analysis -- Automated Segmentation of Multiple Sclerosis Lesions using Multi-Dimensional Gated Recurrent Units -- Joint Intensity Fusion Image Synthesis Applied to Multiple Sclerosis Lesion Segmentation -- MARCEL (inter-Modality Ane Registration with CorELation ratio): An Application for Brain Shift Correction in Ultrasound-Guided Brain Tumor Resection -- Generalised Wasserstein Dice Score for Imbalanced Multi-class Segmentation using Holistic Convolutional Networks -- Overall Survival Time Prediction for High Grade Gliomas based on Sparse Representation Framework -- Traumatic Brain Lesion Quantication based on Mean Diusivity Changes -- Pairwise, Ordinal Outlier Detection of Traumatic Brain Injuries -- Sub-Acute & Chronic Ischemic Stroke Lesion MRI Segmentation -- Brain Tumor Segmentation Using an Adversarial Network -- Brain Cancer Imaging Phenomics Toolkit (brain-CaPTk): An Interactive Platform for Quantitative Analysis of Glioblastoma -- Brain Tumor Image Segmentation -- Deep Learning based Multimodal Brain Tumor Diagnosis -- Multimodal Brain Tumor Segmentation using Ensemble of Forest Method -- Pooling-free fully convolutional networks with dense skip connections for semantic segmentation, with application to brain tumor segmentation -- Automatic Brain Tumor Segmentation using Cascaded Anisotropic Convolutional Neural Networks -- 3D Brain Tumor Segmentation through Integrating Multiple 2D FCNNs -- MRI Brain Tumor Segmentation and Patient Survival Prediction using Random Forests and Fully Convolutional Networks -- Automatic Segmentation and Overall Survival Prediction in Gliomas using Fully Convolutional Neural Network and Texture Analysis -- Multimodal Brain Tumor Segmentation Using 3D Convolutional Networks -- A Conditional Adversarial Network for Semantic Segmentation of Brain Tumor -- Dilated Convolutions for Brain Tumor Segmentation in MRI Scans -- Residual Encoder and Convolutional Decoder Neural Network for Glioma Segmentation -- TPCNN: Two-phase Patch-based Convolutional Neural Network for Automatic Brain Tumor Segmentation and Survival Prediction -- Brain Tumor Segmentation and Radiomics Survival Prediction: Contribution to the BRATS 2017 Challenge -- Multi-modal PixelNet for Brain Tumor Segmentation -- Brain Tumor Segmentation using Dense Fully Convolutional Neural Network -- Brain Tumor Segmentation in MRI Scans using Deeply-Supervised Neural Networks -- Brain Tumor Segmentation and Parsing on MRIs using Multiresolution Neural Networks -- Brain Tumor Segmentation using Deep Fully Convolutional Neural Networks -- Glioblastoma and Survival Prediction -- MRI Augmentation via Elastic Registration for Brain Lesions Segmentation -- Cascaded V-Net using ROI masks for brain tumor segmentation -- Brain Tumor Segmentation using a 3D FCN with Multi-Scale Loss -- Brain tumor segmentation using a multi-path CNN based method -- 3D Deep Neural Network-Based Brain Tumor Segmentation Using Multimodality Magnetic Resonance Sequences -- Automated Brain Tumor Segmentation on Magnetic Resonance Images (MRIs) and Patient Overall Survival Prediction using Support Vector Machines -- Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation -- Tumor segmentation from multimodal MRI using random forest with superpixel and tensor based feature extraction -- Towards Uncertainty-assisted Brain Tumor Segmentation and Survival Prediction -- Ischemic Stroke Lesion Image Segmentation -- WMH Segmentation Challenge: a Texture-based Classication Approach -- White Matter Hyperintensities Segmentation In a Few Seconds Using Fully Convolutional Network and Transfer Learning.
Record Nr. UNISA-996465306103316
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries [[electronic resource] ] : First International Workshop, Brainles 2015, Held in Conjunction with MICCAI 2015, Munich, Germany, October 5, 2015, Revised Selected Papers / / edited by Alessandro Crimi, Bjoern Menze, Oskar Maier, Mauricio Reyes, Heinz Handels
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries [[electronic resource] ] : First International Workshop, Brainles 2015, Held in Conjunction with MICCAI 2015, Munich, Germany, October 5, 2015, Revised Selected Papers / / edited by Alessandro Crimi, Bjoern Menze, Oskar Maier, Mauricio Reyes, Heinz Handels
Edizione [1st ed. 2016.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Descrizione fisica 1 online resource (IX, 298 p. 117 illus.)
Disciplina 006.42
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Optical data processing
Pattern recognition
Artificial intelligence
Algorithms
Application software
Computer graphics
Image Processing and Computer Vision
Pattern Recognition
Artificial Intelligence
Algorithm Analysis and Problem Complexity
Information Systems Applications (incl. Internet)
Computer Graphics
ISBN 3-319-30858-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Brain lesion image analysis -- Brain tumor image segmentation -- Ischemic stroke lesion image segmentation.
Record Nr. UNINA-9910482985003321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries [[electronic resource] ] : First International Workshop, Brainles 2015, Held in Conjunction with MICCAI 2015, Munich, Germany, October 5, 2015, Revised Selected Papers / / edited by Alessandro Crimi, Bjoern Menze, Oskar Maier, Mauricio Reyes, Heinz Handels
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries [[electronic resource] ] : First International Workshop, Brainles 2015, Held in Conjunction with MICCAI 2015, Munich, Germany, October 5, 2015, Revised Selected Papers / / edited by Alessandro Crimi, Bjoern Menze, Oskar Maier, Mauricio Reyes, Heinz Handels
Edizione [1st ed. 2016.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Descrizione fisica 1 online resource (IX, 298 p. 117 illus.)
Disciplina 006.42
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Optical data processing
Pattern recognition
Artificial intelligence
Algorithms
Application software
Computer graphics
Image Processing and Computer Vision
Pattern Recognition
Artificial Intelligence
Algorithm Analysis and Problem Complexity
Information Systems Applications (incl. Internet)
Computer Graphics
ISBN 3-319-30858-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Brain lesion image analysis -- Brain tumor image segmentation -- Ischemic stroke lesion image segmentation.
Record Nr. UNISA-996466002603316
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries [[electronic resource] ] : Second International Workshop, BrainLes 2016, with the Challenges on BRATS, ISLES and mTOP 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 17, 2016, Revised Selected Papers / / edited by Alessandro Crimi, Bjoern Menze, Oskar Maier, Mauricio Reyes, Stefan Winzeck, Heinz Handels
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries [[electronic resource] ] : Second International Workshop, BrainLes 2016, with the Challenges on BRATS, ISLES and mTOP 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 17, 2016, Revised Selected Papers / / edited by Alessandro Crimi, Bjoern Menze, Oskar Maier, Mauricio Reyes, Stefan Winzeck, Heinz Handels
Edizione [1st ed. 2016.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Descrizione fisica 1 online resource (XI, 292 p. 110 illus.)
Disciplina 616.99281
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Computer vision
Pattern recognition systems
Artificial intelligence
Algorithms
Data mining
Medical informatics
Computer Vision
Automated Pattern Recognition
Artificial Intelligence
Data Mining and Knowledge Discovery
Health Informatics
ISBN 3-319-55524-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Brain Lesion -- Brain Tumor Segmentation (BRATS) -- I schemic Stroke Lesion Image Segmentation (ISLES), Mild Traumatic Brain Injury Outcome Prediction (mTOP).
Record Nr. UNISA-996465720603316
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries [[electronic resource] ] : Second International Workshop, BrainLes 2016, with the Challenges on BRATS, ISLES and mTOP 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 17, 2016, Revised Selected Papers / / edited by Alessandro Crimi, Bjoern Menze, Oskar Maier, Mauricio Reyes, Stefan Winzeck, Heinz Handels
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries [[electronic resource] ] : Second International Workshop, BrainLes 2016, with the Challenges on BRATS, ISLES and mTOP 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 17, 2016, Revised Selected Papers / / edited by Alessandro Crimi, Bjoern Menze, Oskar Maier, Mauricio Reyes, Stefan Winzeck, Heinz Handels
Edizione [1st ed. 2016.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Descrizione fisica 1 online resource (XI, 292 p. 110 illus.)
Disciplina 616.99281
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Computer vision
Pattern recognition systems
Artificial intelligence
Algorithms
Data mining
Medical informatics
Computer Vision
Automated Pattern Recognition
Artificial Intelligence
Data Mining and Knowledge Discovery
Health Informatics
ISBN 3-319-55524-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Brain Lesion -- Brain Tumor Segmentation (BRATS) -- I schemic Stroke Lesion Image Segmentation (ISLES), Mild Traumatic Brain Injury Outcome Prediction (mTOP).
Record Nr. UNINA-9910484913603321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Medical Computer Vision [[electronic resource] ] : Recognition Techniques and Applications in Medical Imaging / / edited by Bjoern Menze, Georg Langs, Zhuowen Tu, Antonio Criminisi
Medical Computer Vision [[electronic resource] ] : Recognition Techniques and Applications in Medical Imaging / / edited by Bjoern Menze, Georg Langs, Zhuowen Tu, Antonio Criminisi
Edizione [1st ed. 2011.]
Pubbl/distr/stampa Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2011
Descrizione fisica 1 online resource (XI, 226 p. 100 illus., 80 illus. in color.)
Disciplina 006.6
006.37
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Optical data processing
Artificial intelligence
Image Processing and Computer Vision
Artificial Intelligence
ISBN 3-642-18421-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Shape, geometry and registration -- Markov models for image reconstruction and analysis -- Automatic anatomy localization via classification -- Texture analysis -- Segmentation.
Record Nr. UNISA-996465579303316
Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2011
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Medical Computer Vision and Bayesian and Graphical Models for Biomedical Imaging [[electronic resource] ] : MICCAI 2016 International Workshops, MCV and BAMBI, Athens, Greece, October 21, 2016, Revised Selected Papers / / edited by Henning Müller, B. Michael Kelm, Tal Arbel, Weidong Cai, M. Jorge Cardoso, Georg Langs, Bjoern Menze, Dimitris Metaxas, Albert Montillo, William M. Wells III, Shaoting Zhang, Albert C.S. Chung, Mark Jenkinson, Annemie Ribbens
Medical Computer Vision and Bayesian and Graphical Models for Biomedical Imaging [[electronic resource] ] : MICCAI 2016 International Workshops, MCV and BAMBI, Athens, Greece, October 21, 2016, Revised Selected Papers / / edited by Henning Müller, B. Michael Kelm, Tal Arbel, Weidong Cai, M. Jorge Cardoso, Georg Langs, Bjoern Menze, Dimitris Metaxas, Albert Montillo, William M. Wells III, Shaoting Zhang, Albert C.S. Chung, Mark Jenkinson, Annemie Ribbens
Edizione [1st ed. 2017.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Descrizione fisica 1 online resource (XIII, 222 p. 75 illus.)
Disciplina 610.28
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Optical data processing
Health informatics
Artificial intelligence
Mathematical statistics
Computer science—Mathematics
Pattern recognition
Image Processing and Computer Vision
Health Informatics
Artificial Intelligence
Probability and Statistics in Computer Science
Math Applications in Computer Science
Pattern Recognition
ISBN 3-319-61188-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Constructing Subject- and Disease-Specific Effect Maps: Application to Neurodegenerative Diseases -- BigBrain: Automated Cortical Parcellation and Comparison with Existing Brain Atlases -- LATEST: Local AdapTivE and Sequential Training for Tissue Segmentation of Isointense Infant Brain MR Images -- Landmark-based Alzheimer's Disease Diagnosis Using Longitudinal Structural MR Images -- Inferring Disease Status by non-Parametric Probabilistic Embedding -- A Lung Graph-Model for Pulmonary Hypertension and Pulmonary Embolism Detection on DECT Images -- Explaining Radiological Emphysema Subtypes with Unsupervised Texture Prototypes: MESA COPD Study -- Automatic Segmentation of Abdominal MRI Using Selective Sampling and Random Walker -- Gaze2Segment: A Pilot Study for Integrating Eye-Tracking Technology into Medical Image Segmentation -- Automatic Detection of Histological Artifacts in Mouse Brain Slice Images -- Lung Nodule Classification by Jointly Using Visual Descriptors and Deep Features -- Representation Learning for Cross-Modality Classification -- Guideline-based Machine Learning for Standard Plane Extraction in 3D Cardiac Ultrasound -- A Statistical Model for Simultaneous Template Estimation, Bias Correction, and Registration of 3D Brain Images -- Bayesian Multiview Manifold Learning Applied to Hippocampus Shape and Clinical Score Data -- Rigid Slice-To-Volume Medical Image Registration through Markov Random Fields -- Sparse Probabilistic Parallel Factor Analysis for the Modeling of PET and Task-fMRI data -- Non-local Graph-based Regularization for Deformable Image Registration -- Unsupervised Framework for Consistent Longitudinal MS Lesion Segmentation. .
Record Nr. UNINA-9910483568703321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Medical Computer Vision and Bayesian and Graphical Models for Biomedical Imaging [[electronic resource] ] : MICCAI 2016 International Workshops, MCV and BAMBI, Athens, Greece, October 21, 2016, Revised Selected Papers / / edited by Henning Müller, B. Michael Kelm, Tal Arbel, Weidong Cai, M. Jorge Cardoso, Georg Langs, Bjoern Menze, Dimitris Metaxas, Albert Montillo, William M. Wells III, Shaoting Zhang, Albert C.S. Chung, Mark Jenkinson, Annemie Ribbens
Medical Computer Vision and Bayesian and Graphical Models for Biomedical Imaging [[electronic resource] ] : MICCAI 2016 International Workshops, MCV and BAMBI, Athens, Greece, October 21, 2016, Revised Selected Papers / / edited by Henning Müller, B. Michael Kelm, Tal Arbel, Weidong Cai, M. Jorge Cardoso, Georg Langs, Bjoern Menze, Dimitris Metaxas, Albert Montillo, William M. Wells III, Shaoting Zhang, Albert C.S. Chung, Mark Jenkinson, Annemie Ribbens
Edizione [1st ed. 2017.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Descrizione fisica 1 online resource (XIII, 222 p. 75 illus.)
Disciplina 610.28
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Optical data processing
Health informatics
Artificial intelligence
Mathematical statistics
Computer science—Mathematics
Pattern recognition
Image Processing and Computer Vision
Health Informatics
Artificial Intelligence
Probability and Statistics in Computer Science
Math Applications in Computer Science
Pattern Recognition
ISBN 3-319-61188-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Constructing Subject- and Disease-Specific Effect Maps: Application to Neurodegenerative Diseases -- BigBrain: Automated Cortical Parcellation and Comparison with Existing Brain Atlases -- LATEST: Local AdapTivE and Sequential Training for Tissue Segmentation of Isointense Infant Brain MR Images -- Landmark-based Alzheimer's Disease Diagnosis Using Longitudinal Structural MR Images -- Inferring Disease Status by non-Parametric Probabilistic Embedding -- A Lung Graph-Model for Pulmonary Hypertension and Pulmonary Embolism Detection on DECT Images -- Explaining Radiological Emphysema Subtypes with Unsupervised Texture Prototypes: MESA COPD Study -- Automatic Segmentation of Abdominal MRI Using Selective Sampling and Random Walker -- Gaze2Segment: A Pilot Study for Integrating Eye-Tracking Technology into Medical Image Segmentation -- Automatic Detection of Histological Artifacts in Mouse Brain Slice Images -- Lung Nodule Classification by Jointly Using Visual Descriptors and Deep Features -- Representation Learning for Cross-Modality Classification -- Guideline-based Machine Learning for Standard Plane Extraction in 3D Cardiac Ultrasound -- A Statistical Model for Simultaneous Template Estimation, Bias Correction, and Registration of 3D Brain Images -- Bayesian Multiview Manifold Learning Applied to Hippocampus Shape and Clinical Score Data -- Rigid Slice-To-Volume Medical Image Registration through Markov Random Fields -- Sparse Probabilistic Parallel Factor Analysis for the Modeling of PET and Task-fMRI data -- Non-local Graph-based Regularization for Deformable Image Registration -- Unsupervised Framework for Consistent Longitudinal MS Lesion Segmentation. .
Record Nr. UNISA-996466465403316
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Medical Computer Vision. Large Data in Medical Imaging [[electronic resource] ] : Third International MICCAI Workshop, MCV 2013, Nagoya, Japan, September 26, 2013, Revised Selected Papers / / edited by Bjoern Menze, Georg Langs, Albert Montillo, Michael Kelm, Henning Müller, Zhuowen Tu
Medical Computer Vision. Large Data in Medical Imaging [[electronic resource] ] : Third International MICCAI Workshop, MCV 2013, Nagoya, Japan, September 26, 2013, Revised Selected Papers / / edited by Bjoern Menze, Georg Langs, Albert Montillo, Michael Kelm, Henning Müller, Zhuowen Tu
Edizione [1st ed. 2014.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014
Descrizione fisica 1 online resource (XI, 229 p. 93 illus.)
Disciplina 610.2856
Collana Image Processing, Computer Vision, Pattern Recognition, and Graphics
Soggetto topico Optical data processing
Pattern recognition
Health informatics
Image Processing and Computer Vision
Pattern Recognition
Health Informatics
ISBN 3-319-05530-5
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Overview of the 2013 Workshop on Medical Computer Vision -- Semi-supervised Learning of Nonrigid Deformations for Image Registration -- Local Regression Learning via Forest Classification For 2D/3D Deformable Registration -- Flexible Architecture for Streaming and Visualization of Large Virtual Microscopy Images -- 2D-PCA Shape Models: Application to 3D Reconstruction of the Human Teeth from a Single Image -- Class-Specific Regression Random Forest for Accurate Extraction of Standard Planes from 3D Echocardiography -- Accurate Whole-Brain Segmentation for Alzheimer's Disease Combining an Adaptive Statistical Atlas and Multi-atlas -- Integrated Spatio-Temporal Segmentation of Longitudinal Brain Tumor Imaging Studies -- Robust Mixture-Parameter Estimation for Unsupervised Segmentation of Brain MR Images -- White Matter Supervoxel Segmentation by Axial DP-Means Clustering -- Semantic Context Forests for Learning-Based Knee Cartilage Segmentation in 3D MR Images -- Local Phase-Based Fast Ray Features for Automatic Left Ventricle Apical View Detection in 3D Echocardiography -- Automatic Aorta Detection in 3D Cardiac CT Images Using Bayesian Tracking Method -- Organ Localization Using Joint AP/LAT View Landmark Consensus Detection and Hierarchical Active Appearance Models -- Pectoral Muscle Detection in Digital Breast Tomosynthesis and Mammography -- Multilevel Image Feature Learning for Computer-Aided Diagnosis on Large-Scale Evaluation -- Shape Curvature Histogram: A Shape Feature for Celiac Disease Diagnosis -- 2D–Based 3D Volume Retrieval Using Singular Value Decomposition of Detected Regions -- Feature Extraction with Intrinsic Distortion Correction in Celiac Disease Imagery: No Need for Rasterization -- A Novel Shape Feature Descriptor for the Classification of Polyps in HD Colonoscopy -- Multi-Structure Atlas-Based Segmentation Using Anatomical Regions of Interest -- Using Probability Maps for Multi-organ Automatic Segmentation.
Record Nr. UNISA-996203274903316
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui