Robust shape-constrained active contour for whole heart segmentation in 3-D CT images for radiotherapy planning

Xuan Zhao, Yao Wang, Gabor Jozsef

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Automatic segmentation of the whole heart in computed tomography(CT) image is crucial for efficient treatment planning of thoracic radiotherapy. In this paper, we propose a fully automatic method for whole heart segmentation of thoracic CT images. A robust active shape model (Robust ASM) is proposed using shape models developed from training data to reduce outliers due to similar intensity of neighboring organs. A novel shape constrained active contour model is presented to further improve the segmentation result. A mean point-to-surface error of 2.37mm was measured based on 38 images. The averaged Dice index is 0.90.

Original languageEnglish (US)
Title of host publication2014 IEEE International Conference on Image Processing, ICIP 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-5
Number of pages5
ISBN (Electronic)9781479957514
DOIs
StatePublished - Jan 28 2014

Publication series

Name2014 IEEE International Conference on Image Processing, ICIP 2014

Keywords

  • CT image
  • Radiotherapy
  • Whole heart segmentation

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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    Zhao, X., Wang, Y., & Jozsef, G. (2014). Robust shape-constrained active contour for whole heart segmentation in 3-D CT images for radiotherapy planning. In 2014 IEEE International Conference on Image Processing, ICIP 2014 (pp. 1-5). [7024999] (2014 IEEE International Conference on Image Processing, ICIP 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICIP.2014.7024999