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Proceedings Paper

Matching structural images of the human brain using statistical and geometrical image features
Author(s): James C. Gee; Christian Barillot; Lionel Le Briquer; David R. Haynor; Ruzena K. Bajcsy
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Paper Abstract

The efficacy of using intensity edges, curvature of iso-intensity contours, and tissue classified data for image matching are examined. The image matching problem is formulated in such a way that the different features are handled uniformly, allowing the same code to be used in each instance. The results using both simulated and real brain images indicate that each feature affected and improvement in the correspondence after matching with it.

Paper Details

Date Published: 9 September 1994
PDF: 14 pages
Proc. SPIE 2359, Visualization in Biomedical Computing 1994, (9 September 1994); doi: 10.1117/12.185179
Show Author Affiliations
James C. Gee, Lab. SIM and Univ. of Pennsylvania (United States)
Christian Barillot, Lab. SIM (France)
Lionel Le Briquer, Lab. SIM (France)
David R. Haynor, Univ. of Washington (United States)
Ruzena K. Bajcsy, Lab. SIM and Univ. of Pennsylvania (United States)


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

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