ArticleIEEE transactions on medical imaging2021
Reconstructing Undersampled Photoacoustic Microscopy Images Using Deep Learning.
Article in IEEE transactions on medical imaging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers.
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Who cites it
63 citing papers in PubMed.
- A Model-Based Joint Feature Fusion framework for limited-view photoacoustic tomography reconstruction.Photoacoustics · 2026Article
- PAT-Mamba: Adaptive all-in-one image restoration for photoacoustic tomography via state space model.Photoacoustics · 2026Article
- Ultrasound-Based Tomographic Imaging Reconstruction and Synthesis Methods: a Scoping Review.Journal of imaging informatics in medicine · 2026Article
- VITAL: Value-Invariant Transformation and Alignment Learning for quantitative photoacoustic microscopy.Photoacoustics · 2026Article
- Ultraviolet Sensing-Guided Biomedical Systems: From Label-Free Imaging to Dosimetry and Therapy Feedback.Biosensors · 2026Review
- Progressive dual-branch adversarial diffusion for sparse-view photoacoustic tomography reconstruction.Photoacoustics · 2026Article
- Photoacoustic Imaging for Women's Gynecological Health: Advances and Clinical Prospects.Bioengineering (Basel, Switzerland) · 2026Review
- Photoacoustic Fingerprinting for Robust Molecular Imaging.bioRxiv : the preprint server for biology · 2026Article
- Improved Sensitivity in Large Field of View Multispectral Laser-Scanning Photoacoustic Microscopy for Measuring Oxygen Saturation In Vivo.Journal of biophotonics · 2026Article
- Photoacoustic Microscopy for Multiscale Biological System Visualization and Clinical Translation.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Spectral-distortion-suppressed deep learning for fiber sensor photoacoustic microscopy.Photoacoustics · 2025Article
- Reduction of photobleaching effects in photoacoustic imaging using noise agnostic, platform-flexible deep-learning methods.Journal of biomedical optics · 2025Article
- Wavelet-enhanced residual optimal transport for Mamba-based image restoration in photoacoustic tomography.Photoacoustics · 2025Article
- Adaptive Run-Length Encoded DCT: A High-Fidelity Compression Algorithm for Real-Time Photoacoustic Microscopy Imaging in LabVIEW.Journal of biophotonics · 2025Article
- 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
- Structure and oxygen saturation recovery of sparse photoacoustic microscopy images by deep learning.Photoacoustics · 2025Article
- Hybrid transformer-CNN network-driven optical-scanning undersampling for photoacoustic remote sensing microscopy.Photoacoustics · 2025Article
- An enhanced image restoration using deep learning and transformer based contextual optimization algorithm.Scientific reports · 2025Article
3 more citing papers are in PubMed but not listed here.
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Authors and funding
8 authors.
Funding
Abstract
One primary technical challenge in photoacoustic microscopy (PAM) is the necessary compromise between spatial resolution and imaging speed. In this study, we propose a novel application of deep learning principles to reconstruct undersampled PAM images and transcend the trade-off between spatial resolution and imaging speed. We compared various convolutional neural network (CNN) architectures, and selected a Fully Dense U-net (FD U-net) model that produced the best results. To mimic various undersampling conditions in practice, we artificially downsampled fully-sampled PAM images of mouse brain vasculature at different ratios. This allowed us to not only definitively establish the ground truth, but also train and test our deep learning model at various imaging conditions. Our results and numerical analysis have collectively demonstrated the robust performance of our model to reconstruct PAM images with as few as 2% of the original pixels, which can effectively shorten the imaging time without substantially sacrificing the image quality.
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Registered trials
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