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

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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.

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Acknowledgements

The authors would like to thanks Dr. Jyotsna Sen, Sr. Professor, department of radiodiagnosis, Pt. B. D. Sharma Postgraduate Institute of Medical Sciences, Rohtak, for stimulating discussions regarding different sonographic characteristics exhibited by various types of benign and malignant thyroid tumors. The first author acknowledge “National Project Implementation Unit (NPIU), a unit of Ministry of Human Resource Development, Government of India” for the financial assistantship through TEQIP-III project at Deenbandhu Chhotu Ram University of Science and Technology, Murthal, Haryana, India.

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  1. Department of Electronics and Communication Engineering, Deenbandhu Chhotu Ram University of Science and Technology Murthal, Sonepat, 131039, India

    Niranjan Yadav & Rajeshwar Dass

  2. Central Scientific Instruments Organization, Council of Scientific and Industrial Research, Chandigarh, 160030, India

    Jitendra Virmani

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  1. Niranjan Yadav
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  2. Rajeshwar Dass
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Correspondence to Niranjan Yadav.

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Yadav, N., Dass, R. & Virmani, J. A systematic review of machine learning based thyroid tumor characterisation using ultrasonographic images. J Ultrasound (2024). https://doi.org/10.1007/s40477-023-00850-z

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