Automatic segmentation of different pathologies from cardiac cine MRI using registration and multiple component em estimation

Wenzhe Shi, Xiahai Zhuang, Haiyan Wang, Simon Duckett, Declan Oregan, Philip Edwards, Sebastien Ourselin, Daniel Rueckert

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

17 Scopus citations

Abstract

In this paper, we develop a framework for the automatic detection and segmentation of the ventricle and myocardium from multi-slice, short-axis cine MR images. The segmentation framework has the ability to deal with large shape variability of the heart, poorly defined boundaries and abnormal intensity distribution of the myocardium (e.g. due to infarcts). We integrate a series of state-of-the-art techniques into a fully automatic workflow, including a detection algorithm for the LV, atlas-based segmentation, and intensity-based refinement using a Gaussian mixture model that is optimized using the Expectation Maximization (EM) algorithm and the graph cut algorithm. We evaluate this framework on three different patient groups, one with infarction, one with left ventricular hypertrophy (both are common result of cardiovascular diseases) and another group of subjects with normal heart anatomy. Results indicate that the proposed method is capable of producing segmentation results that show good robustness and high accuracy (Dice 0.908±0.025 for the endocardial and 0.946±0.016 for the epicardial segmentations) across all patient groups with and without pathology.

Original languageEnglish
Title of host publicationFunctional Imaging and Modeling of the Heart - 6th International Conference, FIMH 2011, Proceedings
Pages163-170
Number of pages8
DOIs
StatePublished - 2011
Externally publishedYes
Event6th International Conference on Functional Imaging and Modeling of the Heart, FIMH 2011 - New York City, NY, United States
Duration: 25 May 201127 May 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6666 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference6th International Conference on Functional Imaging and Modeling of the Heart, FIMH 2011
Country/TerritoryUnited States
CityNew York City, NY
Period25/05/1127/05/11

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