Medical Computer Vision: Algorithms for Big Data: International Workshop, MCV 2014, Held in Conjunction with MICCAI 2014, Cambridge, MA, USA, September 18, 2014, Revised Selected Papers

✍ Scribed by Bjoern Menze, Georg Langs, Albert Montillo, Michael Kelm, Henning Müller, Shaoting Zhang, Weidong (Tom) Cai, Dimitris Metaxas (eds.)

• Publisher: Springer International Publishing
• Year: 2014
• Tongue: English
• Leaves: 213
• Series: Lecture Notes in Computer Science 8848 Image Processing, Computer Vision, Pattern Recognition, and Graphics
• Edition: 1
• Category: Library

✦ Synopsis

This book constitutes the thoroughly refereed post-workshop proceedings of the International Workshop on Medical Computer Vision: Algorithms for Big Data, MCV 2014, held in Cambridge, MA, USA, in September 2019, in conjunction with the 17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014. The one-day workshop aimed at exploring the use of modern computer vision technology and "big data" algorithms in tasks such as automatic segmentation and registration, localization of anatomical features and detection of anomalies emphasizing questions of harvesting, organizing and learning from large-scale medical imaging data sets and general-purpose automatic understanding of medical images. The 18 full and 1 short papers presented in this volume were carefully reviewed and selected from 30 submission.

✦ Table of Contents

Front Matter....Pages I-XI
Front Matter....Pages 1-1
Overview of the 2014 Workshop on Medical Computer Vision—Algorithms for Big Data (MCV 2014)....Pages 3-10
Front Matter....Pages 11-11
Joint Segmentation and Registration for Infant Brain Images....Pages 13-21
LINKS: Learning-Based Multi-source IntegratioN FrameworK for Segmentation of Infant Brain Images....Pages 22-33
Pectoralis Muscle Segmentation on CT Images Based on Bayesian Graph Cuts with a Subject-Tailored Atlas....Pages 34-44
Front Matter....Pages 45-45
Learning Features for Tissue Classification with the Classification Restricted Boltzmann Machine....Pages 47-58
Dementia-Related Features in Longitudinal MRI: Tracking Keypoints over Time....Pages 59-70
Object Classification in an Ultrasound Video Using LP-SIFT Features....Pages 71-81
Unsupervised Pre-training Across Image Domains Improves Lung Tissue Classification....Pages 82-93
Front Matter....Pages 95-95
Atlas-Guided Multi-channel Forest Learning for Human Brain Labeling....Pages 97-104
Fast Multiatlas Selection Using Composition of Transformations for Radiation Therapy Planning....Pages 105-115
Classifier-Based Multi-atlas Label Propagation with Test-Specific Atlas Weighting for Correspondence-Free Scenarios....Pages 116-124
Front Matter....Pages 125-125
CT Prostate Deformable Segmentation by Boundary Regression....Pages 127-136
Precise Lumen Segmentation in Coronary Computed Tomography Angiography....Pages 137-147
Confidence-Based Training for Clinical Data Uncertainty in Image-Based Prediction of Cardiac Ablation Targets....Pages 148-159
Front Matter....Pages 161-161
Rule-Based Ventral Cavity Multi-organ Automatic Segmentation in CT Scans....Pages 163-170
Multi-atlas Segmentation and Landmark Localization in Images with Large Field of View....Pages 171-180
Automatic Liver Segmentation Using Statistical Prior Models and Free-form Deformation....Pages 181-188
Hierarchic Multi–atlas Based Segmentation for Anatomical Structures: Evaluation in the VISCERAL Anatomy Benchmarks....Pages 189-200
Automatic 3D Multiorgan Segmentation via Clustering and Graph Cut Using Spatial Relations and Hierarchically-Registered Atlases....Pages 201-209
Back Matter....Pages 211-211

✦ Subjects

Image Processing and Computer Vision; Pattern Recognition; User Interfaces and Human Computer Interaction; Computer Graphics; Simulation and Modeling