The role of artificial intelligence in the differential thyroid nodules ultrasound diagnostics

A. Trukhin, S. M. Zakharova, M. Y. Dunaev, M. P. Isaeva, A. Garmash, E. Troshina
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Abstract

Advances in the development and improvement of medical technologies and methods of processing medical images make it possible to highlight clinically significant characteristics that were not previously available to classical methods of medical imaging. Ultrasound diagnostics of thyroid gland nodules has a huge potential medical images processing. The article presents an overview of the existing ultrasound classification systems for thyroid nodules malignancy and the prospects for the development of intellectual tools TIRADS (Thyroid Imaging Reporting and Data System) classification system.
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人工智能在甲状腺结节鉴别超声诊断中的作用
医学技术的发展和改进以及处理医学图像的方法的进步,使得突出以前经典医学成像方法无法获得的临床重要特征成为可能。超声诊断甲状腺结节具有巨大的医学图像处理潜力。本文综述了现有甲状腺结节恶性肿瘤超声分类系统,并对智能工具甲状腺影像报告与数据系统(TIRADS)分类系统的发展前景进行了展望。
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Associations of thyroid status and thyroperoxidase antibodies with serum trace elements Features of achieving compensation of hypothyroisis in pregnant women Structural and morphologic characteristics of nodular goiter in chronic iodine deficiency status Investigation of neural network models application in EU-TIRADS thyroid nodules classification for personalization of thyroid gland ultrasound diagnostic Press release from the Endocrine Society ENDO 2022 Annual Conference
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