4D shape priors for a level set segmentation of the left myocardium in SPECT sequences

Timo Kohlberger, Daniel Cremers, Mikaël Rousson, Ramamani Ramaraj, Gareth Funka-Lea

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

35 Scopus citations

Abstract

We develop a 4D (3D plus time) statistical shape model for implicit level set based shape representations. To this end, we represent hand segmented training sequences of the left ventricle by respective 4-dimensional embedding functions and approximate these by a principal component analysis. In contrast to recent 4D models on explicit shape representations, the implicit shape model developed in this work does not require the computation of point correspondences which is known to be quite challenging, especially in higher dimensions. Experimental results on the segmentation of SPECT sequences of the left myocardium confirm that the 4D shape model outperforms respective 3D models, because it takes into account a statistical model of the temporal shape evolution.

Original languageEnglish
Title of host publicationMedical Image Computing and Computer-Assisted Intervention, MICCAI 2006 - 9th International Conference, Proceedings
PublisherSpringer Verlag
Pages92-100
Number of pages9
ISBN (Print)3540447075, 9783540447078
DOIs
StatePublished - 2006
Externally publishedYes
Event9th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2006 - Copenhagen, Denmark
Duration: 1 Oct 20066 Oct 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4190 LNCS - I
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference9th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2006
Country/TerritoryDenmark
CityCopenhagen
Period1/10/066/10/06

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