Automated detection scheme of architectural distortion in mammograms using adaptive Gabor filter

Ruriha Yoshikawa, Atsushi Teramoto, Tomoko Matsubara, Hiroshi Fujita

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)


Breast cancer is a serious health concern for all women. Computer-aided detection for mammography has been used for detecting mass and micro-calcification. However, there are challenges regarding the automated detection of the architectural distortion about the sensitivity. In this study, we propose a novel automated method for detecting architectural distortion. Our method consists of the analysis of the mammary gland structure, detection of the distorted region, and reduction of false positive results. We developed the adaptive Gabor filter for analyzing the mammary gland structure that decides filter parameters depending on the thickness of the gland structure. As for post-processing, healthy mammary glands that run from the nipple to the chest wall are eliminated by angle analysis. Moreover, background mammary glands are removed based on the intensity output image obtained from adaptive Gabor filter. The distorted region of the mammary gland is then detected as an initial candidate using a concentration index followed by binarization and labeling. False positives in the initial candidate are eliminated using 23 types of characteristic features and a support vector machine. In the experiments, we compared the automated detection results with interpretations by a radiologist using 50 cases (200 images) from the Digital Database of Screening Mammography (DDSM). As a result, true positive rate was 82.72%, and the number of false positive per image was 1.39. There results indicate that the proposed method may be useful for detecting architectural distortion in mammograms.

Original languageEnglish
Title of host publicationMedical Imaging 2013
Subtitle of host publicationComputer-Aided Diagnosis
Publication statusPublished - 2013
EventMedical Imaging 2013: Computer-Aided Diagnosis - Lake Buena Vista, FL, United States
Duration: 12-02-201314-02-2013

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X


OtherMedical Imaging 2013: Computer-Aided Diagnosis
Country/TerritoryUnited States
CityLake Buena Vista, FL

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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