A novel deep learning model for breast lesion classification using ultrasound Images: A multicenter data evaluation.

Journal: Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Published Date: Mar 4, 2023

Abstract

PURPOSE: Breast cancer is one of the major reasons of death due to cancer in women. Early diagnosis is the most critical key for disease screening, control, and reducing mortality. A robust diagnosis relies on the correct classification of breast lesions. While breast biopsy is referred to as the "gold standard" in assessing both the activity and degree of breast cancer, it is an invasive and time-consuming approach.

Authors

  • Nasim Sirjani
    Research and Development Department, Med Fanavarn Plus Co., Karaj, Iran.
  • Mostafa Ghelich Oghli
    Research and Development Department, Med Fanavarn Plus Co., Karaj, Iran; Department of Cardiovascular Sciences, KU Leuven, Leuven, Belgium. Electronic address: m.g31_mesu@yahoo.com.
  • Mohammad Kazem Tarzamni
    Department of Radiology, Imam Reza Hospital, Tabriz University of Medical Sciences, Tabriz, Iran.
  • Masoumeh Gity
    Department of Radiology, School of Medicine, Advanced Diagnostic and Interventional Radiology Research Center (ADIR), Imam Khomeini Hospital, Tehran University of Medical Sciences, Tehran, Iran.
  • Ali Shabanzadeh
    Research and Development Department, Med Fanavarn Plus Co., Karaj, Iran. Electronic address: shabanzadeh.ali@gmail.com.
  • Payam Ghaderi
    Research and Development Department, Med Fanavarn Plus Co., Karaj, Iran.
  • Isaac Shiri
    Biomedical and Health Informatics, Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Sciences, Tehran, Iran.
  • Ardavan Akhavan
    Research and Development Department, Med Fanavarn Plus Co., Karaj, Iran.
  • Mehri Faraji
    Research and Development Department, Med Fanavaran Plus Co., Karaj, Iran.
  • Mostafa Taghipour
    Department of Biomedical Engineering, Kermanshah University of Medical Sciences, Kermanshah, Iran.

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