Optimization of active-contour model parameters using genetic algorithms: segmentation of breast lesions in mammograms

Yuan Xu; Scott Neu; Chester J. Ornes; Janis F. Owens; Jack Sklansky; Daniel J. Valentino

doi:10.1117/12.467106

9 May 2002 Optimization of active-contour model parameters using genetic algorithms: segmentation of breast lesions in mammograms

Yuan Xu, Scott Neu, Chester J. Ornes, Janis F. Owens, Jack Sklansky, Daniel J. Valentino

Author Affiliations +

Proceedings Volume 4684, Medical Imaging 2002: Image Processing; (2002) https://doi.org/10.1117/12.467106
Event: Medical Imaging 2002, 2002, San Diego, California, United States

Abstract

Genetic algorithms (GA's) were used to find optimal sets of parameters for an active contour model (ACM) algorithm that segments breast lesions in mammography images. These parameters, which are typically determined empirically, are used in an energy function that is minimized by the ACM algorithm when producing a segmentation contour. Using manually segmented contours supplied by experienced radiologists, GA techniques were used to vary the parameter values until the contours produced by the ACM algorithm closely matched those of the radiologists.

Citation Download Citation

Yuan Xu, Scott Neu, Chester J. Ornes, Janis F. Owens, Jack Sklansky, and Daniel J. Valentino "Optimization of active-contour model parameters using genetic algorithms: segmentation of breast lesions in mammograms", Proc. SPIE 4684, Medical Imaging 2002: Image Processing, (9 May 2002); https://doi.org/10.1117/12.467106

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