Artificial intelligence in thyroid ultrasound

Frontiers in Oncology

Oncology

Xin-Wu Cui¹  Ting-Ting Du²  Ya Xu²  Jin Tong²  Jing Cheng²  Qiao-Li Li³  Wen-Xiao Li³  Jun Li³  Li-Nan Shi³  Chun-Li Cao³ 

[1] Department of Medical Ultrasound, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China;Department of Ultrasound, The First Affiliated Hospital of Shihezi University, Shihezi, China;Department of Ultrasound, The First Affiliated Hospital of Shihezi University, Shihezi, China;NHC Key Laboratory of Prevention and Treatment of Central Asia High Incidence Diseases, First Affiliated Hospital, School of Medicine, Shihezi University, Shihezi, China;

关键词: artificial intelligence;    thyroid;    ultrasound;    machine learning;    deep learning;   

DOI  :  10.3389/fonc.2023.1060702

 received in 2022-10-03, accepted in 2023-04-07,  发布年份 2023

来源: Frontiers

【 摘 要 】

Artificial intelligence (AI), particularly deep learning (DL) algorithms, has demonstrated remarkable progress in image-recognition tasks, enabling the automatic quantitative assessment of complex medical images with increased accuracy and efficiency. AI is widely used and is becoming increasingly popular in the field of ultrasound. The rising incidence of thyroid cancer and the workload of physicians have driven the need to utilize AI to efficiently process thyroid ultrasound images. Therefore, leveraging AI in thyroid cancer ultrasound screening and diagnosis cannot only help radiologists achieve more accurate and efficient imaging diagnosis but also reduce their workload. In this paper, we aim to present a comprehensive overview of the technical knowledge of AI with a focus on traditional machine learning (ML) algorithms and DL algorithms. We will also discuss their clinical applications in the ultrasound imaging of thyroid diseases, particularly in differentiating between benign and malignant nodules and predicting cervical lymph node metastasis in thyroid cancer. Finally, we will conclude that AI technology holds great promise for improving the accuracy of thyroid disease ultrasound diagnosis and discuss the potential prospects of AI in this field.

【 授权许可】

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Copyright © 2023 Cao, Li, Tong, Shi, Li, Xu, Cheng, Du, Li and Cui