2007
DOI: 10.1155/2007/10526
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Brain MRI Segmentation with Multiphase Minimal Partitioning: A Comparative Study

Abstract: This paper presents the implementation and quantitative evaluation of a multiphase three-dimensional deformable model in a level set framework for automated segmentation of brain MRIs. The segmentation algorithm performs an optimal partitioning of three-dimensional data based on homogeneity measures that naturally evolves to the extraction of different tissue types in the brain. Random seed initialization was used to minimize the sensitivity of the method to initial conditions while avoiding the need f… Show more

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Cited by 24 publications
(12 citation statements)
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“…FSGPC-II has AOMs of 93% and degree of equality of 88% for WM, which is better than that research, although no a priori information is utilized. Angelini et al [22] gave a best minimum error rate of 13.5% while comparing many algorithms. FSGPC-II favors this research by achieving a misclassification rate of 4.8% and 7.7% as evaluated by different experts.…”
Section: Discussion Of Comparison With Expertsmentioning
confidence: 99%
“…FSGPC-II has AOMs of 93% and degree of equality of 88% for WM, which is better than that research, although no a priori information is utilized. Angelini et al [22] gave a best minimum error rate of 13.5% while comparing many algorithms. FSGPC-II favors this research by achieving a misclassification rate of 4.8% and 7.7% as evaluated by different experts.…”
Section: Discussion Of Comparison With Expertsmentioning
confidence: 99%
“…Let X={X 1 ly of sites with regard to a lique c is a singleton or all neighbours. If c is not a (3) family of random variables variable taking values in the The family X is a random = Λ M .…”
Section: B Markov Random Fieldmentioning
confidence: 99%
“…the object (or the foreground) and the background. In order to simultaneously segment multiple objects, similar to level-set framework [19,24,25], more than one deformable model could be introduced at the same time. In order to realize simultaneous multi-object segmentation, these deformable models will be coupled together via some mechanism, such as distance [25] or multi-phase fashion [17,24].…”
Section: Myocardial Segmentation In High Speed Mrimentioning
confidence: 99%