Three-dimensional C-scan-based generation adversarial network with synthetic input to improve optical coherence tomography angiography Article Swipe

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Jingjiang Xu , Zhongwu Feng , Haixia Qiu , Peijun Tang , Kai Gao , Yanping Huang , Gongpu Lan , Jia Qin , Lin An , Gangyong Jia , Q. M. Jonathan Wu ·

YOU? · · 2025 · Open Access · · DOI: https://doi.org/10.1117/1.jbo.30.5.056006

It demonstrates that the proposed 3DCS-GAN can greatly improve vascular visualization in the deep layer, provide better image quality than the multiple averaged OCTA images, and achieve superior image enhancement for volumetric OCTA data.

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Optical coherence tomography Computer science Angiography Coherence (philosophical gambling strategy) Tomography Optics Optical coherence tomography angiography Artificial intelligence Adversarial system Radiology Physics Medicine Quantum mechanics

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Type: article
Language: en
Landing Page: https://doi.org/10.1117/1.jbo.30.5.056006
OA Status: gold
Related Works: 10
OpenAlex ID: https://openalex.org/W4410264748

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