Machine learning techniques for breast cancer computer aided diagnosis using different image modalities: A systematic review.

Journal: Computer methods and programs in biomedicine
Published Date: Dec 12, 2017

Abstract

BACKGROUND AND OBJECTIVE: The high incidence of breast cancer in women has increased significantly in the recent years. Physician experience of diagnosing and detecting breast cancer can be assisted by using some computerized features extraction and classification algorithms. This paper presents the conduction and results of a systematic review (SR) that aims to investigate the state of the art regarding the computer aided diagnosis/detection (CAD) systems for breast cancer.

Authors

  • Nisreen I R Yassin
    Systems & Information Department, Engineering Research Division, National Research Centre, Dokki, Cairo 12311, Egypt. Electronic address: eng_nesrin@hotmail.com.
  • Shaimaa Omran
    Systems & Information Department, Engineering Research Division, National Research Centre, Dokki, Cairo 12311, Egypt. Electronic address: shmomran@gmail.com.
  • Enas M F El Houby
    Systems & Information Department, Engineering Research Division, National Research Centre, Dokki, Cairo 12311, Egypt. Electronic address: em.fahmy@nrc.sci.eg.
  • Hemat Allam
    Anaesthesia & Pain, Medical Division, National Research Centre, Dokki, Cairo 12311, Egypt. Electronic address: allamhemat@gmail.com.

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