MSAC U-net: multiscale AC block convolutional neural networks for blood vessel segmentation in fundus images

Ge Deng; Shi-Long Shi; Zhi-Yuan Guan; Y He; X. Qiu

doi:10.53388/bmec2025024

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MSAC U-net: multiscale AC block convolutional neural networks for blood vessel segmentation in fundus images

Ge Deng Shi-Long Shi Zhi-Yuan Guan Y He X. Qiu

Year: 2025 Journal: Biomedical Engineering Communications Vol: 4 (4)Pages: 24-24

DOI: 10.53388/bmec2025024

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Keywords:

Convolutional neural network Fundus (uterus) Block (permutation group theory) Segmentation Artificial intelligence Computer science Pattern recognition (psychology) Ophthalmology Internal medicine Medicine Mathematics Combinatorics

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Retinal Imaging and Analysis

Health Sciences → Medicine → Radiology, Nuclear Medicine and Imaging

Brain Tumor Detection and Classification

Life Sciences → Neuroscience → Neurology

MSAC U-net: multiscale AC block convolutional neural networks for blood vessel segmentation in fundus images

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