Automatic scoliosis angle measurement using deep learning methods, how far we are from clinical application: A narrative review

Authors

  • Dima Kh. I. Kassab St. Petersburg State University, 7–9, Universitetskaya nab., St. Petersburg, 199034, Russian Federation
  • Irina G. Kamyshanskaya St. Petersburg State University, 7–9, Universitetskaya nab., St. Petersburg, 199034, Russian Federation
  • Andrei Pershin Federal Scientific Center of Rehabilitation of the Disabled named after G. A. Albrecht of the Ministry of Labour and Social Protection of the Russian Federation, 50, Bestuzhevskaya ul., St. Petersburg, 195067, Russian Federation

DOI:

https://doi.org/10.21638/spbu11.2021.202

Abstract

In recent years, automatic measurement of scoliosis angle using deep learning (DL) techniques is being studied extensively. The objective of this study is to review and assess the clinical applicability of these new methods. A wide search for English and Russian literature was conducted, 13 studies were included. Although the results of many of the reviewed DL methods in measuring the angle of scoliosis are promising, their clinical implication is by far not possible. There is absence of consensus in many issues regarding these new methods (differences in architecture of the ANN, data set, principle of angle measurement and nature of the reported results). In order to successfully introduce these new methods into clinical practice, more comparative and prospective studies are needed. Also, a multidisciplinary team including technical and medical workers is needed.

 

Keywords:

scoliosis, automated Сobb angle, artificial neural network, deep learning

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References


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Published

2021-06-16

How to Cite

Kassab, D., Kamyshanskaya, I. ., & Pershin, A. (2021). Automatic scoliosis angle measurement using deep learning methods, how far we are from clinical application: A narrative review. Vestnik of Saint Petersburg University. Medicine, 16(2), 85–94. https://doi.org/10.21638/spbu11.2021.202

Issue

Vol. 16 No. 2 (2021)

Section

Oncology

License

Articles of "Vestnik of Saint Petersburg University. Medicine" are open access distributed under the terms of the License Agreement with Saint Petersburg State University, which permits to the authors unrestricted distribution and self-archiving free of charge.