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Proceedings Paper

Difficulties of T1 brain MRI segmentation techniques
Author(s): M. Stella Atkins; Kevin Siu; Benjamin Law; Jeffery J. Orchard; Wilfred L. Rosenbaum
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Paper Abstract

This paper looks at the difficulties that can confound published T1-weighted Magnetic Resonance Imaging (MRI) brain segmentation methods, and compares their strengths and weaknesses. Using data from the Internet Brain Segmentation Repository (IBSR) as a gold standard, we ran three different segmentation methods with and without correcting for intensity inhomogeneity. We then calculated the similarity index between the brain masks produced by the segmentation methods and the mask provided by the IBSR. The intensity histograms under the segmented masks were also analyzed to see if a Bi-Gaussian model could be fit onto T1 brain data. Contrary to our initial beliefs, our study found that intensity based T1-weighted segmentation methods were comparable or even superior to, methods utilizing spatial information. All methods appear to have parameters that need adjustment depending on the data set used. Furthermore, it seems that the methods we tested for intensity inhomogeneity did not improve the segmentations due to the nature of the IBSR data set.

Paper Details

Date Published: 9 May 2002
PDF: 8 pages
Proc. SPIE 4684, Medical Imaging 2002: Image Processing, (9 May 2002); doi: 10.1117/12.467158
Show Author Affiliations
M. Stella Atkins, Simon Fraser Univ. (Canada)
Kevin Siu, Simon Fraser Univ. (Canada)
Benjamin Law, Simon Fraser Univ. (Canada)
Jeffery J. Orchard, Simon Fraser Univ. (Canada)
Wilfred L. Rosenbaum, Simon Fraser Univ. (Canada)


Published in SPIE Proceedings Vol. 4684:
Medical Imaging 2002: Image Processing
Milan Sonka; J. Michael Fitzpatrick, Editor(s)

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