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Regional Classification of Left Ventricular Wall in Small Animal Ultrasound Imaging

  • Daniel Tenbrinck
  • Kathrin Ungru
  • Xiaoyi Jiang
  • Jörg Stypmann
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 404)

Abstract

Heart diseases such as acute myocardial infarction are one of the main death causes in industrial societies today. In general, these diseases are accompanied by physiological changes in the heart, which can give valuable information for future therapy if early recognized by cardiologists. This work proposes a processing pipeline for classification of left ventricle regions in medical ultrasound images of small animals as a first step towards recognition of heart remodeling processes. Based on state-of-the-art methods from computer vision an automatic classification of image regions in healthy and scarred myocardial tissue is realized. The performance of the proposed pipeline is evaluated on real ultrasound data of living mice before and after artificially induced myocardial infarction.

Keywords

Classification tissue characterization high-level segmentation shape prior motion estimation optical flow echocardiography ultrasound imaging 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Daniel Tenbrinck
    • 1
    • 3
  • Kathrin Ungru
    • 1
  • Xiaoyi Jiang
    • 1
    • 2
  • Jörg Stypmann
    • 3
  1. 1.Department of Mathematics and Computer ScienceUniversity of MünsterMünsterGermany
  2. 2.Cluster of Excellence EXC 1003, Cells in Motion (CiM)University of MünsterMünsterGermany
  3. 3.Department of Cardiovascular Medicine, Division of CardiologyUniversity Hospital MünsterMünsterGermany

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