Active shape model with inter-profile modeling paradigm for cardiac right ventricle segmentation

Mohammed Elbaz, Ahmed S. Fahmy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

20 Scopus citations

Abstract

In this work, a novel active shape model (ASM) paradigm is proposed to segment the right ventricle (RV) in cardiac magnetic resonance image sequences. The proposed paradigm includes modifications to two fundamental steps in the ASM algorithm. The first modification includes employing the 2D-Principal Component Analysis (PCA) to capture the inter-profile relations among shape’s neighboring landmarks and then model the inter-profile variations between the training set. The second modification is based on using a multi-stage searching algorithm to find the best profile match based on the best maintained profile’s relations and thus the best shape fitting in an iterative manner. The developed methods are validated using a database of short axis cine bright blood MRI images for 30 subjects with total of 90 images. Our results show that the segmentation error can be reduced by about 0.4 mm and contour overlap increased by about 4% compared to the classical ASM technique with paired Student’s t-test indicates statistical significance to a high degree for our results. Furthermore, comparison with literature shows that the proposed method decreases the RV segmentation error significantly.

Original languageEnglish (US)
Title of host publicationMedical Image Computing and Computer-Assisted Intervention, MICCAI2012 - 15th International Conference, Proceedings
EditorsNicholas Ayache, Herve Delingette, Polina Golland, Kensaku Mori
PublisherSpringer Verlag
Pages691-698
Number of pages8
ISBN (Print)9783642334146
DOIs
StatePublished - 2012
Event15th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2012 - Nice, France
Duration: Oct 1 2012Oct 5 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7510 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference15th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2012
CountryFrance
CityNice
Period10/1/1210/5/12

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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