Efficient Semantic Segmentation of Optical Coherence Tomography Images for Retina Layer Analysis on Edge Devices
- Resource Type
- Conference
- Authors
- Chang, Po-Hsiang; Lu, Cheng-Kai; Tang, Tong Boon; Lin, Chih-Wei
- Source
- 2024 10th International Conference on Applied System Innovation (ICASI) Applied System Innovation (ICASI), 2024 10th International Conference on. :205-207 Apr, 2024
- Subject
- Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Fields, Waves and Electromagnetics
Geoscience
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Adaptation models
Technological innovation
Semantic segmentation
Computational modeling
Optical coherence tomography
Image edge detection
Retina
Lightweight
Optical Coherence Tomography
Retina Layer
- Language
- ISSN
- 2768-4156
This paper introduces a lightweight model customized for semantic segmentation of Optical Coherence Tomography (OCT) images, specifically focusing on retina layer segment semantic segmentation for edge devices. The model strikes a balances between accuracy and computational efficiency, rendering it ideal for real-time deployment on devices with constrained resources.