Medical Computer Vision. Large Data in Medical Imaging : 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.

Format:

Book

Contributor:

Menze, Bjoern, Editor.

Langs, Georg, Editor.

Montillo, Albert., Editor.

Kelm, Michael., Editor.

Müller, Henning, Editor.

Tu, Zhuowen., Editor.

SpringerLink (Online service)

Series:

Computer Science (SpringerNature-11645)

LNCS sublibrary. Image processing, computer vision, pattern recognition, and graphics ; SL 6, 8331

Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 8331

Language:

English

Subjects (All):

Computer vision.

Pattern recognition systems.

Medical informatics.

Computer Vision.

Automated Pattern Recognition.

Health Informatics.

Local Subjects:

Computer Vision.

Automated Pattern Recognition.

Health Informatics.

Physical Description:

1 online resource (XI, 229 pages) : 93 illustrations

Edition:

1st ed. 2014.

Contained In:

Springer Nature eBook

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2014.

System Details:

text file PDF

Summary:

This book constitutes the thoroughly refereed post-workshop proceedings of the Third International Workshop on Medical Computer Vision, MCV 2013, held in Nagoya, Japan, in September 2013 in conjunction with the 16th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2013. The 7 revised full papers and 12 poster papers presented were selected from 25 submissions. They have been organized in topical sections on registration and visualization, segmentation, detection and localization, and features and retrieval. In addition, the volume contains two invited papers describing segmentation task and data set of the VISCERAL benchmark challenge.

Contents:

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.

Other Format:

Printed edition:

ISBN:

978-3-319-05530-5

9783319055305

Access Restriction:

Restricted for use by site license.