Fuzzy fusion operators to combine results of complementary medical image segmentation techniques

Denise Guliato; Rangaraj M. Rangayyan; Walter A. Carnielli; Joao Antonio Zuffo; J. E. Leo Desautels

doi:10.1117/1.1578639

1 July 2003 Fuzzy fusion operators to combine results of complementary medical image segmentation techniques

Denise Guliato, Rangaraj M. Rangayyan, Walter A. Carnielli, Joao Antonio Zuffo, J. E. Leo Desautels

Journal of Electronic Imaging, Vol. 12, Issue 3, (July 2003). https://doi.org/10.1117/1.1578639

The detection of masses and tumors in a mammogram is a difficult problem that could benefit from the use of multiple approaches. We propose an abstract concept of information fusion based on a finite automaton and fuzzy sets to integrate and evaluate results of multiple image segmentation procedures. We give examples on how the method can be applied to the problem of mammographic image segmentation, combining results of region growing and closed-contour detection techniques. We also propose a measure of fuzzyness to assess the agreement between a segmented region and a reference contour. Application of the fusion technique to breast tumor detection in mammograms indicates that the fusion results agree with the reference contours provided by a radiologist to a higher extent than the results of the individual methods.

©(2003) Society of Photo-Optical Instrumentation Engineers (SPIE)

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Denise Guliato, Rangaraj M. Rangayyan, Walter A. Carnielli, Joao Antonio Zuffo, and J. E. Leo Desautels "Fuzzy fusion operators to combine results of complementary medical image segmentation techniques," Journal of Electronic Imaging 12(3), (1 July 2003). https://doi.org/10.1117/1.1578639

Published: 1 July 2003

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