Denoising for optical-resolution photoacoustic microscopy via a score-based diffusion generative model

Wenkang Gong; Yubin Cao; Yiguang Wang; Xianlin Song

doi:10.1117/12.3022561

25 January 2024 Denoising for optical-resolution photoacoustic microscopy via a score-based diffusion generative model

Wenkang Gong, Yubin Cao, Yiguang Wang, Xianlin Song

Proceedings Volume 12972, International Academic Conference on Optics and Photonics (IACOP 2023); 1297208 (2024) https://doi.org/10.1117/12.3022561
Event: International Academic Conference on Optics and Photonics (IACOP 2023), 2023, ONLINE, China

Abstract

Photoacoustic microscopy is a hybrid imaging technique that capitalizes on the photoacoustic effect to enhance imaging processes, achieving precise image reconstruction by eliminating noise within photoacoustic signals. This study introduces an innovative deep learning denoising algorithm based on score-based diffusion generative models. During the forward propagation process, the model acquires a score representation of the prior noise distribution resulting from the diffusion of the photoacoustic image. In the reverse reconstruction process, the noisy photoacoustic image serves as input. Following multiple iterations by the solver, a noise-free photoacoustic image is generated as the output. A predictor-corrector framework, trained during the forward propagation process, is employed to rectify the reverse evolution. This algorithm effectively reduces noise and demonstrates its efficacy in complex denoising challenges, thereby significantly improving the quality of photoacoustic imaging.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Wenkang Gong, Yubin Cao, Yiguang Wang, and Xianlin Song "Denoising for optical-resolution photoacoustic microscopy via a score-based diffusion generative model", Proc. SPIE 12972, International Academic Conference on Optics and Photonics (IACOP 2023), 1297208 (25 January 2024); https://doi.org/10.1117/12.3022561

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