A systematic review of machine learning based thyroid tumor characterisation using ultrasonographic images.

Journal: Journal of ultrasound
Published Date:

Abstract

Ultrasonography is widely used to screen thyroid tumors because it is safe, easy to use, and low-cost. However, it is simultaneously affected by speckle noise and other artifacts, so early detection of thyroid abnormalities becomes difficult for the radiologist. Therefore, various researchers continuously address the limitations of sonography and improve the diagnosis potential of US images for thyroid tissue from the last three decays. Accordingly, the present study extensively reviewed various CAD systems used to classify thyroid tumor US (TTUS) images related to datasets, despeckling algorithms, segmentation algorithms, feature extraction and selection, assessment parameters, and classification algorithms. After the exhaustive review, the achievements and challenges have been reported, and build a road map for the new researchers.

Authors

  • Niranjan Yadav
    Department of Electronics and Communication Engineering, Deenbandhu Chhotu Ram University of Science and Technology Murthal, Sonepat, 131039, India. niranjanyadav97@gmail.com.
  • Rajeshwar Dass
    Department of Electronics and Communication Engineering, Deenbandhu Chhotu Ram University of Science and Technology Murthal, Sonepat, 131039, India.
  • Jitendra Virmani
    Central Scientific Instruments Organization, Council of Scientific and Industrial Research, Chandigarh, 160030, India.