Medical Computer Vision. Large Data in Medical Imaging

1. Front Matter

   Pages I-XI

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2. Workshop Overview

   1. Front Matter

      Pages 1-1

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   2. Overview of the 2013 Workshop on Medical Computer Vision (MCV 2013)

      • Henning Müller, Bjoern H. Menze, Georg Langs, Albert Montillo, B. Michael Kelm, Zhuowen Tu et al.

      Pages 3-10

3. Registration and Visualization

   1. Front Matter

      Pages 11-11

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   2. Semi-supervised Learning of Nonrigid Deformations for Image Registration

      • John A. Onofrey, Lawrence H. Staib, Xenophon Papademetris

      Pages 13-23

   3. Local Regression Learning via Forest Classification for 2D/3D Deformable Registration

      • Chen-Rui Chou, Stephen Pizer

      Pages 24-33

   4. Flexible Architecture for Streaming and Visualization of Large Virtual Microscopy Images

      • Germán Corredor, Marcela Iregui, Viviana Arias, Eduardo Romero

      Pages 34-43

   5. 2D-PCA Shape Models: Application to 3D Reconstruction of the Human Teeth from a Single Image

      • Aly S. Abdelrehim, Aly A. Farag, Ahmed M. Shalaby, Moumen T. El-Melegy

      Pages 44-52

   6. Class-Specific Regression Random Forest for Accurate Extraction of Standard Planes from 3D Echocardiography

      • Kiryl Chykeyuk, Mohammad Yaqub, J. Alison Noble

      Pages 53-62

4. Segmentation

   1. Front Matter

      Pages 63-63

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   2. Accurate Whole-Brain Segmentation for Alzheimer’s Disease Combining an Adaptive Statistical Atlas and Multi-atlas

      • Zhennan Yan, Shaoting Zhang, Xiaofeng Liu, Dimitris N. Metaxas, Albert Montillo, The Australian Imaging Biomarkers and Lifestyle Flagship Study of Ageing

      Pages 65-73

   3. Integrated Spatio-Temporal Segmentation of Longitudinal Brain Tumor Imaging Studies

      • Stefan Bauer, Jean Tessier, Oliver Krieter, Lutz-P. Nolte, Mauricio Reyes

      Pages 74-83

   4. Robust Mixture-Parameter Estimation for Unsupervised Segmentation of Brain MR Images

      • Alfiia Galimzianova, Žiga Špiclin, Boštjan Likar, Franjo Pernuš

      Pages 84-94

   5. White Matter Supervoxel Segmentation by Axial DP-Means Clustering

      • Ryan P. Cabeen, David H. Laidlaw

      Pages 95-104

   6. Semantic Context Forests for Learning-Based Knee Cartilage Segmentation in 3D MR Images

      • Quan Wang, Dijia Wu, Le Lu, Meizhu Liu, Kim L. Boyer, Shaohua Kevin Zhou

      Pages 105-115

5. Detection and Localization

   1. Front Matter

      Pages 117-117

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   2. Local Phase-Based Fast Ray Features for Automatic Left Ventricle Apical View Detection in 3D Echocardiography

      • João S. Domingos, Eduardo Lima, Paul Leeson, J. Alison Noble

      Pages 119-129

   3. Automatic Aorta Detection in Non-contrast 3D Cardiac CT Images Using Bayesian Tracking Method

      • Mingna Zheng, J. Jeffery Carr, Yaorong Ge

      Pages 130-137

   4. Organ Localization Using Joint AP/LAT View Landmark Consensus Detection and Hierarchical Active Appearance Models

      • Qi Song, Albert Montillo, Roshni Bhagalia, V. Srikrishnan

      Pages 138-147

   5. Pectoral Muscle Detection in Digital Breast Tomosynthesis and Mammography

      • Florin C. Ghesu, Michael Wels, Anna Jerebko, Michael Sühling, Joachim Hornegger, B. Michael Kelm

      Pages 148-157

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.

• 3D reconstruction
• CT images
• VISCERAL benchmark
• computer tomography
• computer vision
• image registration
• image segmentation
• machine learning
• medical image analysis
• pattern recognition
• visualization

• Technical University of Munich, ETH, Zürich, Switzerland, Munich, Germany

  Bjoern Menze

• Medical University of Vienna, Vienna, Austria

  Georg Langs

• GE Global Research, Niskayuna, USA

  Albert Montillo

• Siemens AG, Erlangen, Germany

  Michael Kelm

• University of Applied Sciences Western Switzerland, Sierre, Switzerland

  Henning Müller

• University of California, La Jolla, USA

  Zhuowen Tu

Policies and ethics