Sonographic diagnosis of thyroid cancer with support of AI

被引：19

作者：

Verburg, Frederik ^{[1
]}

Reiners, Christoph ^{[2
]}

机构：

[1] Univ Hosp Marburg, Nucl Med, Marburg, Germany

[2] Univ Hosp Wurzburg, Nucl Med, Wurzburg, Germany

来源：

NATURE REVIEWS ENDOCRINOLOGY | 2019年 / 15卷 / 06期

关键词：

DATA SYSTEM; ULTRASOUND; NODULES;

D O I：

10.1038/s41574-019-0204-8

中图分类号：

R5 [内科学];

学科分类号：

1002 ; 100201 ;

摘要：

Thyroid ultrasonography is an important element of clinical thyroid diagnostics. Unfortunately, the results of this technique can vary based on the skill and experience of the operator. A new study suggests that assessment of ultrasound images using artificial intelligence has similar sensitivity and improved specificity compared with the judgement of experienced radiologists.

引用

收藏

页码：319 / 321

页数：4

相关论文

共 10 条

[1] Thyroid Nodule Classification in Ultrasound Images by Fine-Tuning Deep Convolutional Neural Network [J].

Chi, Jianning ;

Walia, Ekta ;

Babyn, Paul ;

Wang, Jimmy ;

Groot, Gary ;

Eramian, Mark .

JOURNAL OF DIGITAL IMAGING, 2017, 30 (04) :477-486

[2] Diagnostic potential of real-time elastography (RTE) and shear wave elastography (SWE) to differentiate benign and malignant thyroid nodules: A systematic review and meta-analysis [J].

Hu, Xiangdong ;

Liu, Yujiang ;

Qian, Linxue .

MEDICINE, 2017, 96 (43)

[3] Diagnosis of thyroid cancer using deep convolutional neural network models applied to sonographic images: a retrospective, multicohort, diagnostic study [J].

Li, Xiangchun ;

Zhang, Sheng ;

Zhang, Qiang ;

Wei, Xi ;

Pan, Yi ;

Zhao, Jing ;

Xin, Xiaojie ;

Qin, Chunxin ;

Wang, Xiaoqing ;

Li, Jianxin ;

Yang, Fan ;

Zhao, Yanhui ;

Yang, Meng ;

Wang, Qinghua ;

Zheng, Ming ;

Zheng, Xiangqian ;

Yang, Xiangming ;

Whitlow, Christopher T. ;

Gurcan, Metin Nafi ;

Zhang, Lun ;

Wang, Xudong ;

Pasche, Boris C. ;

Gao, Ming ;

Zhang, Wei ;

Chen, Kexin .

LANCET ONCOLOGY, 2019, 20 (02) :193-201

[4] Accuracy of three-dimensional ultrasound for thyroid volume measurement in children and adolescents [J].

Lyshchik, A ;

Drozd, V ;

Reiners, C .

THYROID, 2004, 14 (02) :113-120

[5] Assessment of Virtual Touch Tissue Imaging Quantification and the Ultrasound Thyroid Imaging Reporting and Data System in Patients With Thyroid Nodules Referred for Biopsy [J].

Mao, Feng ;

Xu, Hui-Xiong ;

Zhou, Hang ;

Bo, Xiao-Wan ;

Li, Xiao-Long ;

Li, Dan-Dan ;

Liu, Bo-Ji ;

Zhang, Yi-Feng ;

Xu, Jun-Mei ;

Qu, Shen .

JOURNAL OF ULTRASOUND IN MEDICINE, 2018, 37 (03) :725-736

[6] Evaluation of Commonly Used Algorithms for Thyroid Ultrasound Images Segmentation and Improvement Using Machine Learning Approaches [J].

Poudel, Prabal ;

Illanes, Alfredo ;

Sheet, Debdoot ;

Friebe, Michael .

JOURNAL OF HEALTHCARE ENGINEERING, 2018, 2018

[7] Multitask Cascade Convolution Neural Networks for Automatic Thyroid Nodule Detection and Recognition [J].

Song, Wenfeng ;

Li, Shuai ;

Liu, Ji ;

Qin, Hong ;

Zhang, Bo ;

Zhang, Shuyang ;

Hao, Aimin .

IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2019, 23 (03) :1215-1224

[8] Thyroid Imaging Reporting and Data System (TI-RADS): A User's Guide [J].

Tessler, Franklin N. ;

Middleton, William D. ;

Grant, Edward G. .

RADIOLOGY, 2018, 287 (01) :29-36

[9] Meta-analysis of thyroid imaging reporting and data system in the ultrasonographic diagnosis of 10,437 thyroid nodules [J].

Wei, Xi ;

Li, Ying ;

Zhang, Sheng ;

Gao, Ming .

HEAD AND NECK-JOURNAL FOR THE SCIENCES AND SPECIALTIES OF THE HEAD AND NECK, 2016, 38 (02) :309-315

[10] Classifier Model Based on Machine Learning Algorithms: Application to Differential Diagnosis of Suspicious Thyroid Nodules via Sonography [J].

Wu, Hongxun ;

Deng, Zhaohong ;

Zhang, Bingjie ;

Liu, Qianyun ;

Chen, Junyong .

AMERICAN JOURNAL OF ROENTGENOLOGY, 2016, 207 (04) :859-864