Point-guided modeling and segmentation of myocardium for low dose cardiac CT images.

Yixun Liu, Marcelo Souto Nacif, Songtao Liu, Christopher T. Sibley, David A. Bluemke, Ronald M. Summers, Jianhua Yao

Research output: Contribution to journalArticlepeer-review


Cardiac CT is emerging as a preferable modality to detect myocardial stress/rest perfusion; however the insufficient contrast of myocardium on CT image makes its segmentation difficult. In this paper, we present a point-guided modeling and deformable model-based segmentation method. This method first builds a triangular surface model of myocardium through Bézier contour fitting based on a few points selected by clinicians. Then, a deformable model-based segmentation method is developed to refine the segmentation result. The experiments on 8 cases show the accuracy of the segmentation in terms of true positive volume fraction, false positive volume fractions, and average surface distance can reach 91.0%, 0.3%, and 0.6mm, respectively. The comparison between the proposed method and a graph cut-based method is performed. The results demonstrate that this method is effective in improving the accuracy further.

Original languageEnglish (US)
Pages (from-to)5327-5330
Number of pages4
JournalConference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference
StatePublished - 2012
Externally publishedYes

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics


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