ArticlePhotoacoustics2025
Generative priors-constraint accelerated iterative reconstruction for extremely sparse photoacoustic tomography boosted by mean-reverting diffusion model: Towards 8 projections.
Article in Photoacoustics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Article
- Advances in photoacoustic imaging reconstruction and quantitative analysis for biomedical applications.Visual computing for industry, biomedicine, and art · 2026Review
- Edge-Aware Short-Chain Diffusion Enables High-Fidelity Sparse-Sampling Optoacoustic Tomography.BME frontiers · 2026Article
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10 authors.
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Abstract
As a novel non-invasive hybrid biomedical imaging technology, photoacoustic tomography combines the advantages of high contrast of optical imaging and high penetration of acoustic imaging. However, the conventional standard reconstruction methods under sparse view may lead to low-quality image in photoacoustic tomography. To address this problem, an advanced sparse reconstruction method for photoacoustic tomography based on the mean-reverting diffusion model is proposed. By modeling the degradation process from a high-quality image under full-view scanning (512 projections) to a sparse image with stable Gaussian noise (i.e., mean state), a mean-reverting diffusion model is trained to learn prior information of the data distribution. Then the learned prior information is employed to generate a high-quality image from the sparse image by iteratively sampling the noisy state. Blood vessels simulation data and the animal
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