Discriminating solitary cysts from soft tissue lesions in mammography using a pretrained deep convolutional neural network.

Journal: Medical physics
Published Date:

Abstract

PURPOSE: It is estimated that 7% of women in the western world will develop palpable breast cysts in their lifetime. Even though cysts have been correlated with risk of developing breast cancer, many of them are benign and do not require follow-up. We develop a method to discriminate benign solitary cysts from malignant masses in digital mammography. We think a system like this can have merit in the clinic as a decision aid or complementary to specialized modalities.

Authors

  • Thijs Kooi
    Diagnostic Image Analysis Group, Department of Radiology, Radboud University Medical Center, Nijmegen, The Netherlands. Electronic address: thijs.kooi@radboudumc.nl.
  • Bram van Ginneken
    Diagnostic Image Analysis Group, Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands; Fraunhofer Mevis, Bremen, Germany.
  • Nico Karssemeijer
  • Ard den Heeten
    Department of Radiology, University Medical Centre Amsterdam, Amsterdam, The Netherlands.