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Light-weight Retinal Layer Segmentation with Global Reasoning
April 26, 2024, 4:45 a.m. | Xiang He, Weiye Song, Yiming Wang, Fabio Poiesi, Ji Yi, Manishi Desai, Quanqing Xu, Kongzheng Yang, Yi Wan
cs.CV updates on arXiv.org arxiv.org
Abstract: Automatic retinal layer segmentation with medical images, such as optical coherence tomography (OCT) images, serves as an important tool for diagnosing ophthalmic diseases. However, it is challenging to achieve accurate segmentation due to low contrast and blood flow noises presented in the images. In addition, the algorithm should be light-weight to be deployed for practical clinical applications. Therefore, it is desired to design a light-weight network with high performance for retinal layer segmentation. In this …
abstract algorithm arxiv contrast cs.ai cs.cv diseases eess.iv flow global however images layer light low medical optical reasoning segmentation the algorithm tool type
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