Segmentation and Tracking of Myocardial Boundaries Using Dynamic Programming
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- 关键词：Dynamic programming ; Tagged MR image analysis ; Robust PCA ; Deformable contours ; Tracking ; 4D cardiac images ; Tag
- 刊名：Lecture Notes in Computer Science
- 出版年：2017
- 出版时间：2017
- 年：2017
- 卷：10124
- 期：1
- 页码：118-126
- 丛书名：Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges
- ISBN：978-3-319-52718-5
- 卷排序：10124
文摘
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.