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Proceedings Paper

Segmentation of inversion recovery MR images using neural networks: a study on aging
Author(s): John O. Glass; Wilburn E. Reddick; Virginia S. Yo; R. Grant Steen
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Paper Abstract

Clinicians have long desired early detection of neurological abnormality for treatment of brain malignancies. In attempts to address this concern, there are numerous reports publishing normative databases of age-related changes of the brain in healthy controls, many using magnetic resonance imaging (MRI). However, most of the method used to access tissue volumes were subject to observer variability. We developed a Kohonen self-organizing map to automatically segment MR images for reproducible and accurate identification of tissues. The developed method was applied to quantitatively assess subtle volume differences in normal controls due to maturational and degenerative changes. The volumes calculated in the test population of 73 controls agreed with current hypothesizes concerning age-related changes of the brain as determined by linear regression analysis of segmented tissue to age. Percent gray matter and percent white matter, as well as the ratio of gray matter to white matter were all found to be significantly correlated with age. Percent gray matter and the ratio of gray matter to white matter were inversely proportional to age while percent white matter was directly proportional to age. These results suggest the utility of the developed segmentation technique, as well as the clinical application it may hold.

Paper Details

Date Published: 24 June 1998
PDF: 11 pages
Proc. SPIE 3338, Medical Imaging 1998: Image Processing, (24 June 1998); doi: 10.1117/12.310938
Show Author Affiliations
John O. Glass, St. Jude Children's Research Hospital and Univ. of Memphis (United States)
Wilburn E. Reddick, St. Jude Children's Research Hospital and Univ. of Memphis (United States)
Virginia S. Yo, St. Jude Children's Research Hospital (United States)
R. Grant Steen, St. Jude Children's Research Hospital and Univ. of Tennessee (United States)


Published in SPIE Proceedings Vol. 3338:
Medical Imaging 1998: Image Processing
Kenneth M. Hanson, Editor(s)

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