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Proceedings Paper

Dual probabilistic classifier for three-dimensional neuroimaging from MRI data
Author(s): Wieslaw L. Nowinski
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Paper Abstract

The paper addresses 3D neuroimaging from MRI data by using a dual probabilistic classifier. The goals are: to enable to see thru the scalp and skull in order to observe the cortical surface and brain deep structures, to achieve a correct appearance of gyration, and to provide tools easy to use by the medical professional. MRI head data is automatically segmented into two regions: the brain (along with some subarachnoid structures and some pare of the outer CSF filling the sulci and fissures) and the outer structures (including the scalp, skull marrow, dura mater). The brain and the outer structures are classified separately using a probabilistic classifier. A new volume is created so as to eliminate the density overlap between the brain and the outer structures. Color and opacity transfer functions suitable to render the volume are generated automatically based on the density probability plots for both regions. Preliminary results are discussed.

Paper Details

Date Published: 9 September 1994
PDF: 12 pages
Proc. SPIE 2359, Visualization in Biomedical Computing 1994, (9 September 1994); doi: 10.1117/12.185198
Show Author Affiliations
Wieslaw L. Nowinski, National Univ. of Singapore (Singapore)

Published in SPIE Proceedings Vol. 2359:
Visualization in Biomedical Computing 1994
Richard A. Robb, Editor(s)

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