单位：[1]College of Information Science & Technology Beijing University of Chemical Technology Beijing, China[2]College of Mechanical & Electrical Engineering Beijing University of Chemical Technology Beijing, China[3]Department of Interventional Ultrasound China-Japan Friendship Hospital Beijing, China
Hyperparathyroidism (HPT) is a disorder in which the parathyroid glands produce too much parathyroid hormone (PTH), which may lead to hypocalcemic convulsions, cardiomyopathy, hypertension and other diseases, even threaten the lives of patients under certain severe conditions. Since HPT is usually multiple and ectopic with variable symptoms, the diagnosis and location of HPT is a difficult task even for senior radiologists. A transfer learning-based computer-aided diagnosis (CAD) approach is proposed for automated recognition of HPT in this paper. A dataset of the brightness-mode ultrasound images is developed for the HPT recognition, which is usually annotated by senior radiologists. We addressed the HPT recognition using the various computer vision algorithms on the HPT dataset and obtained good performances for all the algorithms. The experimental results demonstrated that the dataset is effective in aiding the diagnosis of HPT.
基金：
Joint Project of BRC-BC (Biomedical Translational Engineering Research Center of BUCT-CJFH) [XK2020-04]
语种：
外文
被引次数：
WOS：
第一作者：
第一作者单位：[1]College of Information Science & Technology Beijing University of Chemical Technology Beijing, China
通讯作者：
推荐引用方式(GB/T 7714)：
Chen Jiabo,Guo Qing,Jiang Zixun,et al.Recognition of Hyperparathyroidism based on Transfer Learning[J].2020 IEEE INTERNATIONAL CONFERENCE on BIOINFORMATICS and BIOMEDICINE.2020,2959-2961.doi:10.1109/BIBM49941.2020.9313516.
APA：
Chen, Jiabo,Guo, Qing,Jiang, Zixun,Wang, Huaqing,Yu, Mingan&Wei, Ying.(2020).Recognition of Hyperparathyroidism based on Transfer Learning.2020 IEEE INTERNATIONAL CONFERENCE on BIOINFORMATICS and BIOMEDICINE,,
MLA：
Chen, Jiabo,et al."Recognition of Hyperparathyroidism based on Transfer Learning".2020 IEEE INTERNATIONAL CONFERENCE on BIOINFORMATICS and BIOMEDICINE .(2020):2959-2961
