A fuzzy-statistical contour model for MRI segmentation and target tracking

Wael Abd-Almageed; Aly El-Osery; Christopher Smith

doi:10.1117/12.541406

15 July 2004 A fuzzy-statistical contour model for MRI segmentation and target tracking

Wael Abd-Almageed, Aly El-Osery, Christopher Smith

Proceedings Volume 5438, Visual Information Processing XIII; (2004) https://doi.org/10.1117/12.541406
Event: Defense and Security, 2004, Orlando, Florida, United States

Abstract

In this paper, a new formulation for the parametric active contour model is presented. The new formulation is based on statistical pattern recognition theory. A hybrid of kernel density estimation and fuzzy logic is used to show that active contours can be thought of as a pattern recognition problem. The proposed approach is used in two different application domains, with different performance requirements, to demonstrate its effectiveness. First, the proposed approach is used for a magnetic resonance image segmentation problem to demonstrate the segmentation accuracy. Second, the contour is used in a target tracking experiment to show its tracking capabilities.

Citation Download Citation

Wael Abd-Almageed, Aly El-Osery, and Christopher Smith "A fuzzy-statistical contour model for MRI segmentation and target tracking", Proc. SPIE 5438, Visual Information Processing XIII, (15 July 2004); https://doi.org/10.1117/12.541406

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