Development of a new case based computer-Aided detection scheme for screening mammography

Maxine Tan, Bin Zheng

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

3 Citations (Scopus)


In this study, we examine a new case based approach to computer-Aided detection (CAD) schemes of screening mammograms based on the computation of many global bilateral asymmetry and mammographic density image based features. The current commercialized CAD schemes have high false positive detection rates, which also have high positive lesion detection correlations with radiologists. Thus, we developed a new global image feature based CAD scheme that can cue the warning sign on the cases with high risk of being positive using an extended feature set of 158 mammographic density and texture based features computed on all four craniocaudal (CC) and mediolateral oblique (MLO) view images. We utilized a modified fast and accurate sequential floating forward selection feature selection algorithm and applied selected features to a 'scoring fusion' artificial neural network (ANN) classification scheme to produce a final case based classification score. We tested our methods using a ten-fold cross-validation scheme on 924 cases (476 cancer and 448 recalled or negative). The area under the receiver operating characteristic curve was AUC = 0.742±0.016. Odds ratios increased from 1 to 15.43 as the CAD-generated case based detection scores increased. The results of the study show that useful information can be derived from the global mammographic density image based features that can be examined further as a new paradigm/approach of CAD for screening mammograms.

Original languageEnglish
Title of host publicationIECBES 2016 - IEEE-EMBS Conference on Biomedical Engineering and Sciences
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages6
ISBN (Electronic)9781467377911
Publication statusPublished - 2016
EventIEEE-EMBS International Conference on Biomedical Engineering and Sciences (IECBES) 2016 - Kuala Lumpur, Malaysia
Duration: 4 Dec 20168 Dec 2016 (Proceedings)


ConferenceIEEE-EMBS International Conference on Biomedical Engineering and Sciences (IECBES) 2016
Abbreviated titleIECBES 2016
CityKuala Lumpur
Internet address


  • Computer-Aided detection (CAD) of mammograms
  • Full-field digital mammography
  • Global image feature analysis
  • Improvement of screening mammography efficacy

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