Infarct segmentation of the left ventricle using graph-cuts

Karim, Rashed, Chen, Zhong, Obom, Samantha, Ma, Ying-Liang ORCID:, Acheampong, Prince, Gill, Harminder, Gill, Jaspal, Rinaldi, C. Aldo, O'Neill, Mark, Razavi, Reza, Schaeffter, Tobias and Rhode, Kawal S. (2013) Infarct segmentation of the left ventricle using graph-cuts. In: Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges. Lecture Notes in Computer Science . Springer, Berlin, Heidelberg, 71–79. ISBN 978-3-642-36960-5

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Delayed-enhancement magnetic resonance imaging (DE-MRI) is an effective technique for imaging left ventricular (LV) infarct. Existing techniques for LV infarct segmentation are primarily threshold-based making them prone to high user variability. In this work, we propose a segmentation algorithm that can learn from training images and segment based on this training model. This is implemented as a Markov random field (MRF) based energy formulation solved using graph-cuts. A good agreement was found with the Full-Width-at-Half-Maximum (FWHM) technique.

Item Type: Book Section
Faculty \ School: Faculty of Science > School of Computing Sciences
UEA Research Groups: Faculty of Science > Research Groups > Norwich Epidemiology Centre
Faculty of Medicine and Health Sciences > Research Groups > Norwich Epidemiology Centre
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Depositing User: LivePure Connector
Date Deposited: 04 Jan 2023 10:30
Last Modified: 19 May 2023 09:42
DOI: 10.1007/978-3-642-36961-2_9

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