Paper
9 May 2002 Difficulties of T1 brain MRI segmentation techniques
M. Stella Atkins, Kevin Siu, Benjamin Law, Jeffery J. Orchard, Wilfred L. Rosenbaum
Author Affiliations +
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.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
M. Stella Atkins, Kevin Siu, Benjamin Law, Jeffery J. Orchard, and Wilfred L. Rosenbaum "Difficulties of T1 brain MRI segmentation techniques", Proc. SPIE 4684, Medical Imaging 2002: Image Processing, (9 May 2002); https://doi.org/10.1117/12.467158
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CITATIONS
Cited by 12 scholarly publications.
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KEYWORDS
Brain

Image segmentation

Magnetic resonance imaging

Head

Neuroimaging

Data modeling

Evolutionary algorithms

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