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Left atrial segmentation from 3D respiratoryand ecg-gated magnetic resonance angiography

Research output: Chapter in Book/Report/Conference proceedingChapter

Rashed Karim, Henry Chubb, Wieland Staab, Shadman Aziz, R. James Housden, Mark O’Neill, Reza Razavi, Kawal Rhode

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer-Verlag Berlin Heidelberg
Pages155-163
Number of pages9
Volume9126
ISBN (Print)9783319203089, 9783319203089
DOIs
Publication statusPublished - 2015
Event8th International Conference on Functional Imaging and Modeling of the Heart, FIMH 2015 - Maastricht, Netherlands
Duration: 25 Jun 201527 Jun 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9126
ISSN (Print)03029743
ISSN (Electronic)16113349

Conference

Conference8th International Conference on Functional Imaging and Modeling of the Heart, FIMH 2015
CountryNetherlands
CityMaastricht
Period25/06/201527/06/2015

King's Authors

Abstract

Magnetic resonance angiography (MRA) scans provide excellent chamber and venous anatomy. However, they have traditionally been acquired in breath-hold and are not cardiac-gated. This has made it difficult to use them in conjunction with late gadolinium enhancement (LGE) scans for reconstructing fibrosis/scar on 3D left atrium (LA) anatomy. This work proposes an image processing algorithm for segmenting the LA from a novel MRA sequence which is both ECG-gated and respiratorygated allowing reliable 3D reconstructions with LGE. The algorithm implements image partitioning using discrete Morse theory on digital images. It is evaluated in the context of creating 3D reconstructions of scar/fibrosis with LGE.

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