HT-RCM: Hashimoto's Thyroiditis Ultrasound Image Classification Model Based on Res-FCT and Res-CAM-Reference-Cited by-同舟云学术

HT-RCM: Hashimoto's Thyroiditis Ultrasound Image Classification Model Based on Res-FCT and Res-CAM

Published:2024-02 Issue:2 Volume:28 Page:941-951
ISSN:2168-2194
Container-title:IEEE Journal of Biomedical and Health Informatics
language:
Short-container-title:IEEE J. Biomed. Health Inform.

Author:

Jiang Wenchao¹^ORCID,Chen Kang¹^ORCID,Liang Zhipeng¹^ORCID,Luo Tianchun¹^ORCID,Yue Guanghui²^ORCID,Zhao Zhiming³^ORCID,Song Wei⁴^ORCID,Zhao Ling⁴^ORCID,Wen Jianxuan⁴^ORCID

Affiliation:

1. School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, China

2. National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, Health Science Center, School of Biomedical Engineering, Shenzhen University, Shenzhen, China

3. Multiscale Networked Systems research group, University of Amsterdam, Amsterdam, The Netherlands

4. Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong Province, Guangzhou, Guangdong Province, China

Funder

National Natural Scence Foundation of China

Guangdong Natural Science Fund Project

EU H2020 CLARIFY

National Natural Science Foundation of China

Guangdong Basic and Applied Basic Research Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Health Information Management,Electrical and Electronic Engineering,Computer Science Applications,Health Informatics

Link

http://xplorestaging.ieee.org/ielx7/6221020/10422840/10314736.pdf?arnumber=10314736

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. FBENet: Feature-Level Boosting Ensemble Network for Hashimoto's Thyroiditis Ultrasound Image Classification;IEEE Journal of Biomedical and Health Informatics;2024-09

2. Tnc-Net: Automatic Classification for Thyroid Nodules Lesions Using Convolutional Neural Network;IEEE Access;2024