摘要
近年来,甲状腺癌的发病人数不断增加,伴有转移的患者人数也不断增加,甲状腺癌及其远处转移的早期诊断和治疗是降低病死率的重要方法。人工智能(AI)技术飞速发展,其与医疗领域相结合,辅助甲状腺癌的早期诊断。笔者综述了基于深度学习的AI应用于超声图像、细针穿刺细胞学、组织病理学及淋巴结转移诊断甲状腺癌的研究进展,为将来AI应用于甲状腺癌的研究提供指导。
In recent years,the morbidity of thyroid cancer is increasing,and the metastasis of thyroid cancer is also growing,so the early diagnosis and treatment of thyroid cancer and distant metastasis are important methods to reduce mortality.Artificial intelligence(AI),as an emerging science and technology,is developing rapidly.The combination of AI and the medical field can provide an auxiliary role for the early diagnosis of thyroid cancer.This review focuses on the progress of AI based on deep learning for ultrasound images,fine needle puncture cytology,histopathology and lymphatic metastasis in the diagnosis of thyroid cancer.Furthermore,we provide guidance for the future application of AI in relation to thyroid cancer.
作者
陆奕行
章斌
Lu Yixing;Zhang Bin(Department of Nuclear Medicine,the First Affiliated Hospital of Soochow University,Suzhou 215006,China)
出处
《国际放射医学核医学杂志》
2022年第12期760-764,共5页
International Journal of Radiation Medicine and Nuclear Medicine
关键词
甲状腺肿瘤
人工智能
深度学习
诊断
Thyroid neoplasms
Artificial intelligence
Deep learning
Diagnosis
