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Segmentation of the Left Heart Ventricle in Ultrasound Images Using a Region Based Snake

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Author

Editor

  • Sebastien Ourselin
  • David R. Haynor

Summary, in English

Ultrasound imaging of the heart is a non-invasive method widely used for different applications. One of them is to measure the blood volume in the left ventricle at different stages of the heart cycle. This demands a proper segmentation of the left ventricle and a (semi-) automated method would decrease intra-variability as well as workload. This paper presents a semi-automated segmentation method that uses a region based snake. To avoid any unwanted concavities in the segmentations due to the cardiac valve we use two anchor points in the snake that are located to the left and to the right of the cardiac valve respectively. For the possibility of segmentations in different stages of the heart cycle these anchor points are tracked through the cycle. This tracking is based both on the resemblance of a region around the anchor points and a prior model of the movement in the y-direction of the anchor points. The region based snake functional is the sum of two terms, a regularizing term and a data term. It is our data term that is region based since it involves the integration of a two-dimensional subdomain of the image plane. A segmentation of the left ventricle is obtained by minimizing the functional which is done by continuously reshaping the contour until the optimal shape and size is obtained. The developed method shows promising results.

Publishing year

2013

Language

English

Publication/Series

Proceeding of SPIE

Volume

8669

Document type

Conference paper

Publisher

SPIE

Topic

  • Computer Vision and Robotics (Autonomous Systems)
  • Mathematics

Keywords

  • segmentation
  • region based snake
  • ultrasound
  • left heart ventricle

Conference name

SPIE Medical Imaging, 2013

Conference date

2013-02-09 - 2013-02-14

Conference place

Lake Buena Vista (Orlando area), Florida, United States

Status

Published

Research group

  • Mathematical Imaging Group

ISBN/ISSN/Other

  • ISSN: 0277-786X
  • ISSN: 1996-756X
  • ISBN: 9780819494436