Skip to Main content Skip to Navigation
Conference papers

Detecting Architectural Distortion in Mammograms Using a Gabor Filtered Probability Map Algorithm

Abstract : Breast Cancer is a disease that is prevalent in many countries. Computer-Aided detection (CAD) systems have been developed to assist radiologists in detecting breast cancer. This paper discusses an algorithm for architectural distortion (AD) detection with a better sensitivity than the current CAD systems.19 images containing ADs were preprocessed with a median filter and Gabor filters to extract texture information. AD probability maps were generated using a maximum amplitude map and histogram analysis on the orientation map of the Gabor filter response. AD maps were analyzed to select ROIs as potential AD sites.AD map analysis yielded a sensitivity of 79% (15 out of 19 cases of AD were detected) with a false positive per image (FPI) of 18. Future work involves the development of a second stage in the algorithm to reduce the FPI value and application of the algorithm to a different set of database images.
Document type :
Conference papers
Complete list of metadata

Cited literature [8 references]  Display  Hide  Download
Contributor : Hal Ifip Connect in order to contact the contributor
Submitted on : Tuesday, February 7, 2017 - 1:14:53 PM
Last modification on : Thursday, March 5, 2020 - 5:41:33 PM
Long-term archiving on: : Monday, May 8, 2017 - 2:20:37 PM


Files produced by the author(s)


Distributed under a Creative Commons Attribution 4.0 International License



O’tega Ejofodomi, Michael Olawuyi, Don Uche Onyishi, Godswill Ofualagba. Detecting Architectural Distortion in Mammograms Using a Gabor Filtered Probability Map Algorithm. 9th Artificial Intelligence Applications and Innovations (AIAI), Sep 2013, Paphos, Greece. pp.328-335, ⟨10.1007/978-3-642-41142-7_34⟩. ⟨hal-01459674⟩



Record views


Files downloads