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Journal of Electronic Imaging

Fuzzy fusion operators to combine results of complementary medical image segmentation techniques
Author(s): Denise Guliato; Rangaraj M. Rangayyan; Walter A. Carnielli; Joao Antonio Zuffo; J. E. Leo Desautels
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Paper Abstract

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.

Paper Details

Date Published: 1 July 2003
PDF: 11 pages
J. Electron. Imaging. 12(3) doi: 10.1117/1.1578639
Published in: Journal of Electronic Imaging Volume 12, Issue 3
Show Author Affiliations
Denise Guliato, Federal Univ. of Uberlandia (Brazil)
Rangaraj M. Rangayyan, Univ. of Calgary (Canada)
Walter A. Carnielli, Univ. of Campinas (Brazil)
Joao Antonio Zuffo, Univ. de Sao Paulo (Brazil)
J. E. Leo Desautels, Alberta Cancer Board (Canada)


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