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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 ...
May 30, 2020 · In this study, we propose a novel application of deep learning principles to reconstruct undersampled PAM images and transcend the trade-off between spatial ...
In this study, we newly reported deep learning-based fully reconstructing the undersampled 3D PAM data.
“Reconstructing Undersampled Photoacoustic Microscopy Images Using Deep Learning.” IEEE Trans. Medical Imaging, vol. 40, 2021, pp. 562–70. Dblp, doi:10.1109/TMI ...
Jul 23, 2024 · This methodology aims to accelerate photoacoustic microscopy imaging by reconstructing undersampled images using diffusion models. Denoising ...
May 29, 2020 · Our results and numerical analysis have collectively demonstrated the robust performance of our model to reconstruct PAM images with as few as 2 ...
Jun 6, 2020 · In this study, we propose a novel application of deep learning principles to reconstruct undersampled PAM images and transcend the trade-off ...
Spatial sampling density and data size are important determinants of the imaging speed of photoacoustic microscopy (PAM).
May 30, 2020 · Three-dimensional reconstructing undersampled photoacoustic microscopy images using deep learning · Engineering, Computer Science. Photoacoustics.
Oct 10, 2024 · Spatial sampling density and data size are important determinants of the imaging speed of photoacoustic microscopy (PAM).
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