Related Experiment Video
Updated: Jul 6, 2026
Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
Published on: August 30, 2013
Detection of masses in mammograms via statistically based enhancement, multilevel-thresholding segmentation, and
Alfonso Rojas Domínguez1, Asoke K Nandi
1Department of Electrical Engineering & Electronics, The University of Liverpool, Brownlow Hill, Liverpool L69 3GJ, United Kingdom. Alfonso.Rojas@gmail.com
Abstract:
A method for automatic detection of mammographic masses is presented. As part of this method, an enhancement algorithm that improves image contrast based on local statistical measures of the mammograms is proposed. After enhancement, regions are segmented via thresholding at multiple levels, and a set of features is computed from each of the segmented regions. A region-ranking system is also presented that identifies the regions most likely to represent abnormalities based on the features computed. The method was tested on 57 mammographic images of masses from the Mini-MIAS database, and achieved a sensitivity of 80% at 2.3 false-positives per image (average of 0.32 false-positives per image).
