Open AccessGreedy framework for optical flow tracking of myocardium contours
Author(s) -
AlAgamy Ahmed O.,
Khalifa Ayman,
Fahmy Ahmed S.
Publication year - 2014
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2012.0512
Subject(s) - optical flow , tracking (education) , displacement (psychology) , computer science , computer vision , artificial intelligence , flow (mathematics) , set (abstract data type) , greedy algorithm , level set (data structures) , image segmentation , topology (electrical circuits) , segmentation , algorithm , image (mathematics) , pattern recognition (psychology) , mathematics , geometry , combinatorics , psychology , pedagogy , psychotherapist , programming language
Optical flow (OF) tracking of the myocardium contours has a potential in segmenting the myocardium in time sequences of cardiac medical images. Nevertheless, to estimate the displacement field of the contour points, a number of assumptions are required to solve an under‐determined set of optical flow equations. In this work, a new framework is proposed to solve the OF tracking problem using greedy optimisation algorithm. The new framework allows different types of constraints such as motion invariance, shape and topology to be applied in a unified way. The developed methods are applied to a publicly‐available cardiac magnetic resonance imaging dataset containing image sequences for 33 patients. Quantitative evaluation of the results shows high potential of the methods to accurately track and segment the myocardium contours.