Computer-Aided Classification of Breast Lesions Based on US RF Time Series Using a Novel Machine Learning Approach.

Journal: Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
PMID: 39140240

Abstract

OBJECTIVES: One of the most promising adjuncts for screening breast cancer is ultrasound (US) radio-frequency (RF) time series. It has the superiority of not requiring any supplementary equipment over other methods. This research aimed to propound a machine learning (ML) approach for automatically classifying benign, probably benign, suspicious, and malignant breast lesions based on the features extracted from the accumulated US RF time series.

Authors

  • Mahsa Arab
    Faculty of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran.
  • Ali Fallah
    Biomedical Engineering Department, Amirkabir University of Technology, Tehran, Iran. afallah@aut.ac.ir.
  • Saeid Rashidi
    Faculty of Medical Sciences & Technologies, Science & Research Branch, Islamic Azad University, Tehran, Iran.
  • Maryam Mehdizadeh Dastjerdi
    Faculty of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran.
  • Nasrin Ahmadinejad
    Advanced Diagnostic and Interventional Radiology Research Center (ADIR), Tehran University of Medical Sciences (TUMS), Tehran, Iran.

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