Looking for abnormalities using asymmetrical information from bilateral mammogramsDownload PDF

22 Apr 2022, 17:37 (edited 04 Jun 2022)MIDL 2022 Short PapersReaders: Everyone
  • Keywords: Bilateral mammogram, asymmetry attention, breast cancer
  • Abstract: Radiologists commonly compare the bilateral mammograms to detect asymmetric abnormalities. While fibroglandular tissue is normally quite symmetrically distributed, lesions in one breast and will only rarely have a counterpart in the corresponding area of the opposite breast. Motivated by this experience, we explore a model that can learn to detect asymmetrical information from bilateral mammograms and then find the abnormal areas, similar to what a radiologist does. This can increase model performance and interpretability. We evaluate the proposed methods on the popular INBreast dataset and show improved performance in abnormal classification and weakly supervised segmentation tasks.
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  • Paper Type: novel methodological ideas without extensive validation
  • Primary Subject Area: Detection and Diagnosis
  • Secondary Subject Area: Application: Radiology
  • Confidentiality And Author Instructions: I read the call for papers and author instructions. I acknowledge that exceeding the page limit and/or altering the latex template can result in desk rejection.
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