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Proceedings Paper

Fuzzy object detection in 3D medical images
Author(s): He Wang; Tian-ge Zhuang; Dazong Jiang; Heng Zhang; Wan-Yu Liu; A. Bacelar; Isabelle E. Magnin; Gerard Gimenez
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Paper Abstract

3D images are becoming more popular in the medical field. In order to extract desired objects with uncertainties in 3D images, we proposed a novel method to detect fuzzy boundaries with the aid of fuzzy connectivity relation derived from the theory of fuzzy digital topology. A seed point is interactively selected which is definitely inside the desired object, and is assigned an appropriate membership according to the statistic characteristics in its neighborhood, which is called 'seed region'. Memberships of the other points in the image depend not only on their similarity of greylevel to the seed region, but also on their similarity to adjacent voxels. The later may be calculated from a point to the seed region on the basis of a newly defined concept of fuzzy connectivity. After such transformation, a fuzzy boundary is generated corresponding to a characteristic edge point that is selected by experiences or according to the requirement of practical applications. Furthermore, we may take use of skeleton extraction to optimize this boundary. Boundaries extracted like this are ensured to be Jordan. Experiments on some ultrasonic images show satisfying results with smoothed, connective and optimal boundaries.

Paper Details

Date Published: 4 April 1997
PDF: 9 pages
Proc. SPIE 3026, Nonlinear Image Processing VIII, (4 April 1997); doi: 10.1117/12.271118
Show Author Affiliations
He Wang, Shanghai Jiaotong Univ. (United States)
Tian-ge Zhuang, Shanghai Jiaotong Univ. (China)
Dazong Jiang, Shanghai Jiaotong Univ. (China)
Heng Zhang, Shanghai Jiaotong Univ. (China)
Wan-Yu Liu, CNRS (France)
A. Bacelar, CNRS (France)
Isabelle E. Magnin, CNRS (France)
Gerard Gimenez, CNRS (France)

Published in SPIE Proceedings Vol. 3026:
Nonlinear Image Processing VIII
Edward R. Dougherty; Jaakko T. Astola, Editor(s)

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