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. 2026 Jul 1;14:1873901. doi: 10.3389/fcell.2026.1873901

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Copyright © 2026 Hu, Hu, Luo, Jiang, Zheng, Wang, Wang, Wang and Chen.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Flowchart illustrating a retinal image processing pipeline, starting with an original eye image followed by preprocessing, channel separation into grayscale components, convolutional neural network (CNN) downsampling blocks, linear projection, multiple transformer layers, CNN upsampling, and output showing segmentation of blood vessels overlaid on the retinal image. — Flowchart of artificial intelligence-assisted retinal image processing and quantitative analysis.