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We report a sparse coding-based two-stage image processing technique for noise reduction and contrast enhancement in photoacoustic microscopy (PAM). We have assessed the performance of this denoising technique using multi-parametric PAM images acquired at different optical fluence levels in vivo. Our results show that this technique can significantly improve the contrast-to-noise ratio (~7 times) and visibility of the microvasculature in low-fluence noisy images, enabling us to reduce the optical fluence by a factor of 5 while maintaining a similar image quality. Moreover, this technique improves the accuracy of quantitative measurements of blood oxygenation and flow in low-fluence PAM images.
Zhuoying Wang,Yifeng Zhou, andSong Hu
"Sparse coding-based denoising and contrast enhancement in low-fluence multi-parametric photoacoustic microscopy", Proc. SPIE 11642, Photons Plus Ultrasound: Imaging and Sensing 2021, 116421D (5 March 2021); https://doi.org/10.1117/12.2577980
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Zhuoying Wang, Yifeng Zhou, Song Hu, "Sparse coding-based denoising and contrast enhancement in low-fluence multi-parametric photoacoustic microscopy," Proc. SPIE 11642, Photons Plus Ultrasound: Imaging and Sensing 2021, 116421D (5 March 2021); https://doi.org/10.1117/12.2577980