Matching structural images of the human brain using statistical and geometrical image features

James C. Gee; Christian Barillot; Lionel Le Briquer; David R. Haynor; Ruzena K. Bajcsy

doi:10.1117/12.185179

9 September 1994 Matching structural images of the human brain using statistical and geometrical image features

James C. Gee, Christian Barillot, Lionel Le Briquer, David R. Haynor, Ruzena K. Bajcsy

Proceedings Volume 2359, Visualization in Biomedical Computing 1994; (1994) https://doi.org/10.1117/12.185179
Event: Visualization in Biomedical Computing 1994, 1994, Rochester, MN, United States

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.

Citation Download Citation

James C. Gee, Christian Barillot, Lionel Le Briquer, David R. Haynor, and Ruzena K. Bajcsy "Matching structural images of the human brain using statistical and geometrical image features", Proc. SPIE 2359, Visualization in Biomedical Computing 1994, (9 September 1994); https://doi.org/10.1117/12.185179

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