ArticlePhotoacoustics2021
Photoacoustic microscopy with sparse data by convolutional neural networks.
Article in Photoacoustics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- Acquisition-inspired motion artifact modeling and degradation-consistent diffusion restoration in photoacoustic microscopy.Photoacoustics · 2026Article
- Progressive dual-branch adversarial diffusion for sparse-view photoacoustic tomography reconstruction.Photoacoustics · 2026Article
- Bayesian reconstruction of rapidly scanned mid-infrared optoacoustic signals enables fast, label-free chemical microscopy.Science advances · 2025Article
- A comprehensive review of high-performance photoacoustic microscopy systems.Photoacoustics · 2025Review
- High resolution photoacoustic vascular image reconstruction through the fast residual dense generative adversarial network.Photoacoustics · 2025Article
- Hybrid transformer-CNN network-driven optical-scanning undersampling for photoacoustic remote sensing microscopy.Photoacoustics · 2025Article
- Structure and oxygen saturation recovery of sparse photoacoustic microscopy images by deep learning.Photoacoustics · 2025Article
- Lightweight sparse optoacoustic image reconstruction via an attention-driven multi-scale wavelet network.Photoacoustics · 2025Article
- UPAMNet: A unified network with deep knowledge priors for photoacoustic microscopy.Photoacoustics · 2024Article
- High speed innovations in photoacoustic microscopy.Npj imaging · 2024Review
- Sounding out the dynamics: a concise review of high-speed photoacoustic microscopy.Journal of biomedical optics · 2024Review
- Niche preclinical and clinical applications of photoacoustic imaging with endogenous contrast.Photoacoustics · 2023Review
- Non-uniform image reconstruction for fast photoacoustic microscopy of histology imaging.Biomedical optics express · 2023Article
- Photoacoustic imaging with limited sampling: a review of machine learning approaches.Biomedical optics express · 2023Review
- Three-dimensional reconstructing undersampled photoacoustic microscopy images using deep learning.Photoacoustics · 2023Article
- High-fidelity deconvolution for acoustic-resolution photoacoustic microscopy enabled by convolutional neural networks.Photoacoustics · 2022Article
- Photoacoustic imaging aided with deep learning: a review.Biomedical engineering letters · 2022Review
- High-speed photoacoustic microscopy: A review dedicated on light sources.Photoacoustics · 2021Article
- Dual-foci fast-scanning photoacoustic microscopy with 3.2-MHz A-line rate.Photoacoustics · 2021Article
- Sounding out the hidden data: A concise review of deep learning in photoacoustic imaging.Experimental biology and medicine (Maywood, N.J.) · 2021Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The point-by-point scanning mechanism of photoacoustic microscopy (PAM) results in low-speed imaging, limiting the application of PAM. In this work, we propose a method to improve the quality of sparse PAM images using convolutional neural networks (CNNs), thereby speeding up image acquisition while maintaining good image quality. The CNN model utilizes attention modules, residual blocks, and perceptual losses to reconstruct the sparse PAM image, which is a mapping from a 1/4 or 1/16 low-sampling sparse PAM image to a latent fully-sampled one. The model is trained and validated mainly on PAM images of leaf veins, showing effective improvements quantitatively and qualitatively. Our model is also tested using
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