An auxiliary learning network for carotid ultrasound image classification
- Resource Type
- Conference
- Authors
- Ou, Yanghan; Gan, Haitao; Zhou, Ran; Fang, Xiaoyue
- Source
- 2022 China Automation Congress (CAC) Automation Congress (CAC), 2022 China. :3779-3783 Nov, 2022
- Subject
- Aerospace
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Deep learning
Image segmentation
Ultrasonic imaging
Automation
Medical services
Transformers
Multitasking
ultrasonic imaging
carotid plaques
auxiliary task
residual nets
- Language
- ISSN
- 2688-0938
Carotid plaque classification tasks perform an important part in preventing the occurrence of ischemic strokes. Carotid ultrasound images provide a clear picture of the location and status of plaque which helps the professional doctor in the diagnosis of carotid atherosclerosis. However, existing methods ignore the relevance of different carotid plaque tasks. To exploit the different features of carotid ultrasound images, we propose an auxiliary learning framework. The framework uses carotid plaque classification as the primary task and carotid plaque segmentation as an auxiliary task. The framework uses hard parameter sharing to learn the different features of carotid ultrasound images. The results show that the proposed method is beneficial for improving the carotid plaque classification performance.