Review on ultrasonographic diagnosis of thyroid diseases based on deep learning.
10.7507/1001-5515.202302049
- Author:
Fengyuan QI
1
;
Min QIU
2
;
Guohui WEI
1
Author Information
1. College of Intelligence and Information Engineering, Shandong University of Traditional Chinese Medicine, Jinan 250355, P. R. China.
2. Department of Thyroid Surgery, Affiliated Hospital of Jining Medical University, Jining, Shandong 272007, P. R. China.
- Publication Type:Review
- Keywords:
Deep learning;
Multimodal image;
Thyroid disease;
Ultrasonic image
- MeSH:
Humans;
Algorithms;
Deep Learning;
Image Processing, Computer-Assisted/methods*;
Thyroid Diseases/diagnostic imaging*;
Ultrasonography
- From:
Journal of Biomedical Engineering
2023;40(5):1027-1032
- CountryChina
- Language:Chinese
-
Abstract:
In recent years, the incidence of thyroid diseases has increased significantly and ultrasound examination is the first choice for the diagnosis of thyroid diseases. At the same time, the level of medical image analysis based on deep learning has been rapidly improved. Ultrasonic image analysis has made a series of milestone breakthroughs, and deep learning algorithms have shown strong performance in the field of medical image segmentation and classification. This article first elaborates on the application of deep learning algorithms in thyroid ultrasound image segmentation, feature extraction, and classification differentiation. Secondly, it summarizes the algorithms for deep learning processing multimodal ultrasound images. Finally, it points out the problems in thyroid ultrasound image diagnosis at the current stage and looks forward to future development directions. This study can promote the application of deep learning in clinical ultrasound image diagnosis of thyroid, and provide reference for doctors to diagnose thyroid disease.
