Coverart for item
The Resource Brainlesion : glioma, multiple sclerosis, stroke and traumatic brain injuries : third International Workshop, BrainLes 2017, held in conjunction with MICCAI 2017, Quebec City, QC, Canada, September 14, 2017, Revised selected papers, Alessandro Crimi, Spyridon Bakas, Hugo Kuijf, Bjoern Menze, Mauricio Reyes (eds.)

Brainlesion : glioma, multiple sclerosis, stroke and traumatic brain injuries : third International Workshop, BrainLes 2017, held in conjunction with MICCAI 2017, Quebec City, QC, Canada, September 14, 2017, Revised selected papers, Alessandro Crimi, Spyridon Bakas, Hugo Kuijf, Bjoern Menze, Mauricio Reyes (eds.)

Label
Brainlesion : glioma, multiple sclerosis, stroke and traumatic brain injuries : third International Workshop, BrainLes 2017, held in conjunction with MICCAI 2017, Quebec City, QC, Canada, September 14, 2017, Revised selected papers
Title
Brainlesion
Title remainder
glioma, multiple sclerosis, stroke and traumatic brain injuries : third International Workshop, BrainLes 2017, held in conjunction with MICCAI 2017, Quebec City, QC, Canada, September 14, 2017, Revised selected papers
Statement of responsibility
Alessandro Crimi, Spyridon Bakas, Hugo Kuijf, Bjoern Menze, Mauricio Reyes (eds.)
Title variation
BrainLes 2017
Creator
Contributor
Editor
Subject
Genre
Language
eng
Summary
This book constitutes revised selected papers from the Third International MICCAI Brainlesion Workshop, BrainLes 2017, as well as the International Multimodal Brain Tumor Segmentation, BraTS, and White Matter Hyperintensities, WMH, segmentation challenges, which were held jointly at the Medical Image computing for Computer Assisted Intervention Conference, MICCAI, in Quebec City, Canada, in September 2017. The 40 papers presented in this volume were carefully reviewed and selected from 46 submissions. They were organized in topical sections named: brain lesion image analysis; brain tumor image segmentation; and ischemic stroke lesion image segmentation
Member of
Cataloging source
GW5XE
Dewey number
616.8
Illustrations
illustrations
Index
index present
LC call number
RC280.B7
Literary form
non fiction
http://bibfra.me/vocab/lite/meetingDate
2017
http://bibfra.me/vocab/lite/meetingName
BrainLes (Workshop)
Nature of contents
dictionaries
http://library.link/vocab/relatedWorkOrContributorDate
2017
http://library.link/vocab/relatedWorkOrContributorName
  • Crimi, Alessandro
  • Bakas, Spyridon
  • Kuijf, Hugo
  • Menze, Bjoern
  • Reyes, Mauricio
  • International Conference on Medical Image Computing and Computer-Assisted Intervention
Series statement
  • Lecture notes in computer science,
  • LNCS sublibrary. SL 6, Image processing, computer vision, pattern recognition, and graphics
Series volume
10670
http://library.link/vocab/subjectName
  • Brain
  • Brain
  • Cerebrovascular disease
  • Computer Science
  • Image Processing and Computer Vision
  • Artificial Intelligence (incl. Robotics)
  • Probability and Statistics in Computer Science
  • Health Informatics
Label
Brainlesion : glioma, multiple sclerosis, stroke and traumatic brain injuries : third International Workshop, BrainLes 2017, held in conjunction with MICCAI 2017, Quebec City, QC, Canada, September 14, 2017, Revised selected papers, Alessandro Crimi, Spyridon Bakas, Hugo Kuijf, Bjoern Menze, Mauricio Reyes (eds.)
Instantiates
Publication
Note
Includes author index
Antecedent source
unknown
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
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
Control code
SPR1023589499
Dimensions
unknown
Extent
1 online resource (xiii, 517 pages)
File format
unknown
Form of item
online
Isbn
9783319752389
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
c
Other control number
10.1007/978-3-319-75238-9
Other physical details
illustrations.
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
  • on1023589499
  • (OCoLC)1023589499
Label
Brainlesion : glioma, multiple sclerosis, stroke and traumatic brain injuries : third International Workshop, BrainLes 2017, held in conjunction with MICCAI 2017, Quebec City, QC, Canada, September 14, 2017, Revised selected papers, Alessandro Crimi, Spyridon Bakas, Hugo Kuijf, Bjoern Menze, Mauricio Reyes (eds.)
Publication
Note
Includes author index
Antecedent source
unknown
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
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
Control code
SPR1023589499
Dimensions
unknown
Extent
1 online resource (xiii, 517 pages)
File format
unknown
Form of item
online
Isbn
9783319752389
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
c
Other control number
10.1007/978-3-319-75238-9
Other physical details
illustrations.
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
  • on1023589499
  • (OCoLC)1023589499

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