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Intensity-adaptive segmentation of single-echo T1-weighted magnetic resonance images

✍ Scribed by Reza Momenan; Daniel Hommer; Robert Rawlings; Urs Ruttimann; Michael Kerich; Daniel Rio

Publisher
John Wiley and Sons
Year
1997
Tongue
English
Weight
315 KB
Volume
5
Category
Article
ISSN
1065-9471

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✦ Synopsis

A procedure for segmentation of intracranial tissues, including cerebrospinal fluid surrounding the brain, cortical and subcortical gray matter, and white matter, in a T 1 -weighted magnetic resonance image of the brain, has been developed. The proposed method utilizes information from the histogram of pixel intensities of the intracranial image. Based on this information, an unsupervised K-means clustering procedure separates various tissue regions. Information about the approximate location of anatomical regions within the intracranial space is used to detect ventricles and the caudate nuclei. First a description and justification for the procedure is presented. Then the performance of the procedure is evaluated by analysis of variance. In conclusion, the results of applying this procedure to 31 healthy subjects are presented and future improvements are discussed.

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