Healthy and scar myocardial tissue classification in DE-MRI

Xènia Albà*, Rosa M. Figueras I Ventura, Karim Lekadir, Alejandro F. Frangi

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

Abstract

We propose an automatic technique to segment scar and classify the myocardial tissue of the left ventricle from Delay Enhancement (DE) MRI. The method uses multiple region growing with two types of regions and automatic seed initialization. The region growing criteria is based on intensity distance and the seed initialization is based on a thresholding technique. We refine the obtained segmentation with some morphological operators and geometrical constraints to further define the infarcted area. Thanks to the use of two types of regions when performing the region growing, we are able to segment and classify the healthy and pathological tissues. We have also a third type of tissue in our classification, which includes tissue areas that deserve special attention from medical experts: border-zone tissue or myocardial segmentation errors.

Original languageEnglish
Title of host publicationStatistical Atlases and Computational Models of the Heart
Subtitle of host publicationImaging and Modelling Challenges - Third International Workshop, STACOM 2012, Held in Conjunction with MICCAI 2012, Revised Selected Papers
Pages62-70
Number of pages9
DOIs
Publication statusPublished - 2013
Event3rd International Workshop on Statistical Atlases and Computational Models of the Heart: Imaging and Modelling Challenges, STACOM 2012 - Nice, France
Duration: 5 Oct 20125 Oct 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7746 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference3rd International Workshop on Statistical Atlases and Computational Models of the Heart: Imaging and Modelling Challenges, STACOM 2012
Country/TerritoryFrance
CityNice
Period5/10/125/10/12

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