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Proceedings Paper

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

Paper Details

Date Published: 21 May 1999
PDF: 10 pages
Proc. SPIE 3661, Medical Imaging 1999: Image Processing, (21 May 1999); doi: 10.1117/12.348502
Show Author Affiliations
Denise Guliato, Federal Univ. of Uberlandia (Brazil)
Rangaraj M. Rangayyan, Univ. of Calgary (Canada)
Walter A. Carnielli, State Univ. of Campinas (Brazil)
Joao Antonio Zuffo, Escola Politecnica de Sao Paulo (Brazil)
J. E. Leo Desautels, Alberta Cancer Board (Canada)


Published in SPIE Proceedings Vol. 3661:
Medical Imaging 1999: Image Processing
Kenneth M. Hanson, Editor(s)

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