ArticlePhotoacoustics2022
High-resolution photoacoustic microscopy with deep penetration through learning.
Article in Photoacoustics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Quantitative photoacoustic evaluation of graded ischemic stroke and the therapeutic efficacy of low-intensity transcranial ultrasound stimulation.Biomedical optics express · 2026Article
- Photoacoustic Fingerprinting for Robust Molecular Imaging.bioRxiv : the preprint server for biology · 2026Article
- Early identification of umbilical blood flow restriction and maternal placental hypoperfusion with photoacoustic imaging.Photoacoustics · 2026Article
- Improved Sensitivity in Large Field of View Multispectral Laser-Scanning Photoacoustic Microscopy for Measuring Oxygen Saturation In Vivo.Journal of biophotonics · 2026Article
- Advances in photoacoustic imaging reconstruction and quantitative analysis for biomedical applications.Visual computing for industry, biomedicine, and art · 2026Review
- Advanced imaging strategies in cardiac organoids: bridging the gap between structural complexity and functional analysis.Cardiovascular diabetology · 2026Review
- Spectral-distortion-suppressed deep learning for fiber sensor photoacoustic microscopy.Photoacoustics · 2025Article
- High resolution photoacoustic vascular image reconstruction through the fast residual dense generative adversarial network.Photoacoustics · 2025Article
- All-fiber three-wavelength laser for functional photoacoustic microscopy.Photoacoustics · 2025Article
- Photoacoustic thermal-strain measurement towards noninvasive and accurate temperature mapping in photothermal therapy.Photoacoustics · 2024Article
- Probe fusion all-optic OCT-PAM dual-mode imaging system for biomedical imaging.Photoacoustics · 2024Article
- Review of low-cost light sources and miniaturized designs in photoacoustic microscopy.Journal of biomedical optics · 2024Review
- Photoacoustic imaging plus X: a review.Journal of biomedical optics · 2024Review
- Enhanced resolution and sensitivity acoustic-resolution photoacoustic microscopy with semi/unsupervised GANs.Scientific reports · 2023Article
- Recent development of photoacoustic imaging in dentistry: A review on studies over the last decade.The Saudi dental journal · 2023Review
- Functional photoacoustic imaging: from nano- and micro- to macro-scale.Nano convergence · 2023Review
- Azimuth mapping of fibrous tissue in linear dichroism-sensitive photoacoustic microscopy.Photoacoustics · 2023Article
- Homogeneous-resolution photoacoustic microscopy for ultrawide field-of-view neurovascular imaging in Alzheimer's disease.Photoacoustics · 2023Article
- Freehand scanning photoacoustic microscopy with simultaneous localization and mapping.Photoacoustics · 2022Article
- Deep Learning-Powered Bessel-Beam Multiparametric Photoacoustic Microscopy.IEEE transactions on medical imaging · 2022Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Optical-resolution photoacoustic microscopy (OR-PAM) enjoys superior spatial resolution and has received intense attention in recent years. The application, however, has been limited to shallow depths because of strong scattering of light in biological tissues. In this work, we propose to achieve deep-penetrating OR-PAM performance by using deep learning enabled image transformation on blurry living mouse vascular images that were acquired with an acoustic-resolution photoacoustic microscopy (AR-PAM) setup. A generative adversarial network (GAN) was trained in this study and improved the imaging lateral resolution of AR-PAM from 54.0 µm to 5.1 µm, comparable to that of a typical OR-PAM (4.7 µm). The feasibility of the network was evaluated with living mouse ear data, producing superior microvasculature images that outperforms blind deconvolution. The generalization of the network was validated with in vivo mouse brain data. Moreover, it was shown experimentally that the deep-learning method can retain high resolution at tissue depths beyond one optical transport mean free path. Whilst it can be further improved, the proposed method provides new horizons to expand the scope of OR-PAM towards deep-tissue imaging and wide applications in biomedicine.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.