张雅娇,郑雨欣,徐 栋.多模态超声和人工智能技术对甲状腺滤泡性肿瘤鉴别诊断的研究进展[J].肿瘤学杂志,2023,29(11):953-958.
多模态超声和人工智能技术对甲状腺滤泡性肿瘤鉴别诊断的研究进展
Advances on Differential Diagnosis of Thyroid Follicular Tumors with Multimodal Ultrasonography and Artificial Intelligence
投稿时间:2023-07-20  
DOI:10.11735/j.issn.1671-170X.2023.11.B010
中文关键词:  甲状腺肿瘤  滤泡性  多模态超声  人工智能
英文关键词:thyroid tumor  follicular  multimodal ultrasound  artificial intelligence
基金项目:浙江省“尖兵”“领雁”研发攻关计划资助(2023C04039)
作者单位
张雅娇 浙江中医药大学第二临床医学院 
郑雨欣 浙江省肿瘤医院中国科学院杭州医学研究所 
徐 栋 浙江省肿瘤医院中国科学院杭州医学研究所 
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中文摘要:
      摘 要:多模态超声包括灰阶成像、彩色多普勒血流显像、弹性成像、超声造影和超声引导下穿刺活检等超声检查方法。机器学习、深度学习和神经网络是目前人工智能技术在影像图像分析领域中最常用的手段。不同甲状腺滤泡性肿瘤的治疗方案不同,术前准确地诊断甲状腺滤泡性肿瘤有利于患者手术方案和后期诊疗措施的选择。近年来,多模态超声和人工智能技术在医学领域的应用飞速发展,是目前研究的热点。多模态超声和人工智能技术在甲状腺滤泡性肿瘤鉴别诊断中均有很大进展。全文就多模态超声和人工智能技术对甲状腺滤泡性肿瘤鉴别诊断的研究应用及进展进行综述。
英文摘要:
      Abstract: Multimodal ultrasonography includes gray scale imaging, color Doppler flow imaging, elastography, contrast-enhanced ultrasonography and ultrasound-guided puncture biopsy. Machine learning, deep learning and neural networks are the three most widely used artificial intelligence technologies. The thyroid follicular tumors are heterogeneous, including follicular thyroid adenoma,follicular thyroid carcinoma, follicular variant of papillary thyroid carcinoma,etc., and the accurate diagnosis before surgery is crucial for the selection of surgical plan and late treatment measures. In recent years, the application of multimodal ultrasonography and artificial intelligence technology in the medical field has been rapidly developed, which are conducive to differential diagnosis of thyroid follicular tumors. This paper reviews the latest research progress on the application of multimodal ultrasonography and artificial intelligence technology in the differential diagnosis of thyroid follicular tumors.
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