Segmentation and Tracking of Myocardial Boundaries Using Dynamic Programming View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2017-01-24

AUTHORS

Athira J. Jacob , Varghese Alex , Ganapathy Krishnamurthi

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. More... »

PAGES

118-126

Book

TITLE

Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges

ISBN

978-3-319-52717-8
978-3-319-52718-5

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-52718-5_13

DOI

http://dx.doi.org/10.1007/978-3-319-52718-5_13

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1074205109


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