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    • Keywords


      2D-NEO; nonlinear energy operator; HOG; CAD; breast cancer; microcalcifications.

    • Abstract


      Breast cancer is one of the leading causes of cancer deaths among women worldwide. Early diagnosis of breast cancer can help in reducing the mortality rate. The major challenge in the early diagnosis of breast cancer is the fewer number of radiologists available per million population in developing countries. Thetotal number of radiologists is less than 30 in many third world countries. Since majority of the screening mammograms are normal or do not show any cancer signs, there is need of a screening computer-aided diagnosis (CAD) tool that can detect normal mammograms correctly and thereby reduce the burden on radiologists. Thus, a screening CAD is developed that is able to detect microcalcification clusters in mammogram with 100% sensitivity on the subset of DDSM, INbreast and PGIMER-IITKGP databases at lower false positives ascompared with state of the art methods. The synthetic minority over-sampling technique and the majority class under-sampling based on data distribution are used to improve the classifiers performance by reducing the false positives. An approach based on principal component analysis is proposed to further reduce the false positives by removing the vascular calcifications that are not of any clinical significance and may increase the false positives.

    • Author Affiliations



      1. Department of Electronics and Electrical Communication Engineering, Indian Institute of Technology Kharagpur, Kharagpur 721302, India
      2. Department of Radiodiagnosis and Imaging, Post-graduate Institute of Medical Education and Research, Chandigarh 160012, India
      3. EKO CT & MRI Scan Center, Kolkata Medical College, Kolkata 700004, India
    • Dates

  • Sadhana | News

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