A novel quantification method of dense breast from mammography

DOI 1 Citations

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Other Title
  • マンモグラフィのdense breastの自動定量化に関する検討

Abstract

<p>[background] Evaluating dense breast from mammography is a challenging problem in term of objectiveness in breast screening. We developed a novel objective method evaluating dense breast by calculating the density within breast tissue area. [material and method] Mammography images classified as category 1 taken in our institute were collected. For each mammography image, masking image was created to indicate the are of the breast tissue. A total of 197 pair images were trained and tested with U-Net algorithm. Also, a “relative density” was calculated based on a “fat density” within a mammography. By summing the relative density within the breast tissue area, the “breast density” was calculated and evaluated whether each image was classified as dense breast. [result] DICE coefficient reached up to 87.0%. Defining a dense breast as the breast density being greater than 30%, 77% of the images were consistent with that evaluated by human. [conclusion] By using semantic segmentation, we developed a novel method calculating breast density and evaluating dense breast. Using this method, evaluation of dense breast at the breast screening becomes objective and stable.</p>

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Details 詳細情報について

  • CRID
    1390845713074311168
  • NII Article ID
    130007658319
  • DOI
    10.11517/pjsai.jsai2019.0_1p4j1002
  • Text Lang
    ja
  • Data Source
    • JaLC
    • CiNii Articles
    • Crossref
  • Abstract License Flag
    Disallowed

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