Segmentation for mammography classification utilizing deep convolutional neural network.

Journal: BMC medical imaging
Published Date: Dec 18, 2024

Abstract

BACKGROUND: Mammography for the diagnosis of early breast cancer (BC) relies heavily on the identification of breast masses. However, in the early stages, it might be challenging to ascertain whether a breast mass is benign or malignant. Consequently, many deep learning (DL)-based computer-aided diagnosis (CAD) approaches for BC classification have been developed.

Authors

  • Dip Kumar Saha
    Department of Computer Science and Engineering, Stamford University Bangladesh, Siddeswari, Dhaka, Bangladesh.
  • Tuhin Hossain
    Department of Computer Science and Engineering, Jahangirnagar University, Savar, Dhaka, Bangladesh.
  • Mejdl Safran
    Department of Computer Science, College of Computer and Information Sciences, King Saud University, P.O. Box 51178, Riyadh 11543, Saudi Arabia.
  • Sultan Alfarhood
    Department of Computer Science, College of Computer and Information Sciences, King Saud University, P.O. Box 51178, Riyadh 11543, Saudi Arabia.
  • M F Mridha
    Department of Computer Science and Engineering, American International University, Dhaka, Bangladesh.
  • Dunren Che
    School of Computing, Southern Illinois University, Carbondale, IL 62901, USA.

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