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Semi-Automatic Noninvasive Tracking of Local Myocardial Motion using Dynamic Programming based Elastic Model
Author(s) -
Chao Chen,
Wataru Ohyama,
Tetsushi Wakabayashi,
Fumitaka Kimura
Publication year - 2014
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/17686-8546
Subject(s) - computer science , tracking (education) , motion (physics) , dynamic programming , artificial intelligence , computer vision , algorithm , psychology , pedagogy
semi-automatic motion-tracking method for local myocardial tissue on M-mode echocardiograms is proposed in this paper. The proposed method is applicable to estimating myocardial performance in clinics. The M-mode echocardiogram is a type of echocardiogram used in clinics to measure diagnostic indexes. Such as the thickening and thinning of myocardial muscle layers. In order to measure such indexes, doctors are required to manually track myocardial motion. However, tracking myocardial motion by hand is a very tedious and time-consuming process. The proposed method for tracking the motion of myocardial tissue is based on Dynamic Programming (DP). A Myocardial Elastic (ME) Model is employed to reduce the accumulation of velocity error. The experiment has 3 parts: visual inspection, statistical estimation and the analysis of systematic error. The results of these three evaluations indicate that the proposed method can provide more accurate motion tracking and can replace the manual tracking method for doctors in clinics.

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