ArticleBiomedical optics express2021
Dimensionality reduced plug and play priors for improving photoacoustic tomographic imaging with limited noisy data.
Article in Biomedical optics express, 2021. 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.
- Bandwidth Improvement in Ultrasound Image Reconstruction Using Deep Learning Techniques.Healthcare (Basel, Switzerland) · 2022Article
- Looking deep inside tissue with photoacoustic molecular probes: a review.Journal of biomedical optics · 2022Review
- Translational Photoacoustic Imaging for Disease Diagnosis, Monitoring, and Surgical Guidance: introduction to the feature issue.Biomedical optics express · 2021Article
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4 authors.
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Abstract
The reconstruction methods for solving the ill-posed inverse problem of photoacoustic tomography with limited noisy data are iterative in nature to provide accurate solutions. These methods performance is highly affected by the noise level in the photoacoustic data. A singular value decomposition (SVD) based plug and play priors method for solving photoacoustic inverse problem was proposed in this work to provide robustness to noise in the data. The method was shown to be superior as compared to total variation regularization, basis pursuit deconvolution and Lanczos Tikhonov based regularization and provided improved performance in case of noisy data. The numerical and experimental cases show that the improvement can be as high as 8.1 dB in signal to noise ratio of the reconstructed image and 67.98% in root mean square error in comparison to the state of the art methods.
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