Segmentation and Tracking of Myocardial Boundaries Using Dynamic Programming

  • Athira J. Jacob
  • Varghese Alex
  • Ganapathy Krishnamurthi
Conference paper

DOI: 10.1007/978-3-319-52718-5_13

Part of the Lecture Notes in Computer Science book series (LNCS, volume 10124)
Cite this paper as:
Jacob A.J., Alex V., Krishnamurthi G. (2017) Segmentation and Tracking of Myocardial Boundaries Using Dynamic Programming. In: Mansi T., McLeod K., Pop M., Rhode K., Sermesant M., Young A. (eds) Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges. STACOM 2016. Lecture Notes in Computer Science, vol 10124. Springer, Cham

Abstract

Increasing interest in quantification of local myocardial properties throughout the cardiac cycle from tagged MR (tMR) calls for treatment of the cardiac segmentation problem as a spatio-temporal task. The method presented for myocardial segmentation, uses dynamic programming to choose the optimal contour from a set of possible contours subject to maximizing a cost function. Robust Principle Component Analysis (RPCA) is used to decompose the time series into low rank and sparse components and initialization of the contour is done on the low rank approximation. The 3D nature of the images and tag grid location is incorporated into the cost function to get more robust results. 3D+t segmentation of patient data is achieved by propagating contours spatially and temporally. The method is ideal as a pre-processing step in motion quantification and strain rate mapping algorithms.

Keywords

Dynamic programming Tagged MR image analysis Robust PCA Deformable contours Tracking 4D cardiac images Tag 

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Athira J. Jacob
    • 1
  • Varghese Alex
    • 1
  • Ganapathy Krishnamurthi
    • 1
  1. 1.Indian Institute of Technology-MadrasChennaiIndia

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