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Snake with Shifted Window: Learning to Adapt Vessel Pattern for OCTA Segmentation
April 30, 2024, 4:47 a.m. | Xinrun Chen, Mei Shen, Haojian Ning, Mengzhan Zhang, Chengliang Wang, Shiying Li
cs.CV updates on arXiv.org arxiv.org
Abstract: Segmenting specific targets or structures in optical coherence tomography angiography (OCTA) images is fundamental for conducting further pathological studies. The retinal vascular layers are rich and intricate, and such vascular with complex shapes can be captured by the widely-studied OCTA images. In this paper, we thus study how to use OCTA images with projection vascular layers to segment retinal structures. To this end, we propose the SSW-OCTA model, which integrates the advantages of deformable convolutions …
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