Detecting and tracking the left and right heart ventricles via dynamic programming

Davi Geiger, Alok Gupta

Research output: Contribution to journalConference articlepeer-review


Computation of ventricular volume and the diagnostic quantities like ejection-fraction ratio, heart output, mass, etc. requires detection of myocardial boundaries. The problem of segmenting an image into separate regions is one of the most significant problems in vision. Terzopoulos et al., have proposed an approach to detect the contour regions of complex shapes, assuming a user selected an initial contour not very far from the desired solution. We propose an optimal dynamic programming (DP) based method to detect contours. It is exact and not iterative. We first consider a list of uncertainty for each point selected by the user, wherein the point is allowed to move. Then, a search window is created from two consecutive lists. We then apply a dynamic programming (DP) algorithm to obtain the optinmi contour passing through these lists of uncertainty, optimally utilizing the given information. For tracking, the final contour obtained at one frame is sampled and used as initial points for the next frame. Then, the same DP process is applied. We have demonstrated the algorithms on natural objects in a large spectrum of applications, including interactive segmentation of the regions of interest in medical images.

Original languageEnglish (US)
Pages (from-to)391-402
Number of pages12
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - May 11 1994
EventMedical Imaging 1994: Image Processing - Newport Beach, United States
Duration: Feb 13 1994Feb 18 1994

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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