SAM-OCTA: A Fine-Tuning Strategy for Applying Foundation Model OCTA Image Segmentation Tasks
Author:
Affiliation:
1. Chongqing University,College of Computer Science,Chongqing,China
2. Xiang’an Hospital of Xiamen University,Department of Ophthalmology,Xiamen,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10445798/10445803/10446904.pdf?arnumber=10446904
Reference22 articles.
1. A Deep Learning-Based Quality Assessment and Segmentation System with a Large-Scale Benchmark Dataset for Optical Coherence Tomographic Angiography Image Analysis
2. Foveal Avascular Zone Segmentation of Octa Images Using Deep Learning Approach with Unsupervised Vessel Segmentation
3. RPS‐Net: An effective retinal image projection segmentation network for retinal vessels and foveal avascular zone based on OCTA data
4. Segment Anything
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. SAM-OCTA: Prompting Segment-Anything for OCTA Image Segmentation;2024
2. Sam-Octa: Prompting Segment-Anything for Octa Image Segmentation;2024
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