Fuzzy fusion of results of medical image segmentation

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

doi:10.1117/12.348502

21 May 1999 Fuzzy fusion of results of medical image segmentation

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

Proceedings Volume 3661, Medical Imaging 1999: Image Processing; (1999) https://doi.org/10.1117/12.348502
Event: Medical Imaging '99, 1999, San Diego, CA, United States

Abstract

We propose an abstract concept of data fusion based on finite automata and fuzzy sets to integrate and evaluate different sources of information, in particular results of multiple image segmentation procedures. We give an example of how the method may be applied to the problem of mammographic image segmentation to combine results of region growing and closed- contour detection techniques. We further propose a measure of fuzziness to assess the agreement between a segmented region and a reference contour. Results of application to breast tumor detection in mammograms indicate that the fusion results agree with reference contours provided by a radiologist to a higher extent than the results of the individual methods.

Citation Download Citation

Denise Guliato, Rangaraj M. Rangayyan, Walter A. Carnielli, Joao Antonio Zuffo, and J. E. Leo Desautels "Fuzzy fusion of results of medical image segmentation", Proc. SPIE 3661, Medical Imaging 1999: Image Processing, (21 May 1999); https://doi.org/10.1117/12.348502

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