Enhancement and analysis of digital mammograms using fuzzy models

Melanie A. Sutton; James C. Bezdek

doi:10.1117/12.300055

1 March 1998 Enhancement and analysis of digital mammograms using fuzzy models

Melanie A. Sutton, James C. Bezdek

Proceedings Volume 3240, 26th AIPR Workshop: Exploiting New Image Sources and Sensors; (1998) https://doi.org/10.1117/12.300055
Event: 26th AIPR Workshop: Exploiting New Image Sources and Sensors, 1997, Washington, DC, United States

Abstract

This paper describes our work in enhancing and analyzing digital mammograms form the digital database for screening mammography (DDSM). The DDSM will ultimately contain 3000 cases and provides a unique opportunity for researchers form around the world to compare results on a large, diverse data set. However, the size of the database and images within it require careful consideration of memory limitation issues, display device constraints, etc. We address research problems connected with the modification and application of existing fuzzy modeling approaches to this digital mammography domain. Segmentation and edge detection are sued as benchmark applications for the comparisons we make.

Citation Download Citation

Melanie A. Sutton and James C. Bezdek "Enhancement and analysis of digital mammograms using fuzzy models", Proc. SPIE 3240, 26th AIPR Workshop: Exploiting New Image Sources and Sensors, (1 March 1998); https://doi.org/10.1117/12.300055

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