Improved photoacoustic brain imaging using a deep learning protocol

Rayyan Manwar; Xin Li; Sadreddin Mahmoodkalayeh; Eishi Asano; Dongxiao Zhu; Kamran Avanaki

doi:10.1117/12.2581238

11 March 2021 Improved photoacoustic brain imaging using a deep learning protocol

Rayyan Manwar, Xin Li, Sadreddin Mahmoodkalayeh, Eishi Asano, Dongxiao Zhu, Kamran Avanaki

Proceedings Volume 11642, Photons Plus Ultrasound: Imaging and Sensing 2021; 116423Q (2021) https://doi.org/10.1117/12.2581238
Event: SPIE BiOS, 2021, Online Only

Conference Poster

Abstract

One of the key limitations for the clinical translation of photoacoustic imaging is its penetration depth, which is linked to the tissue maximum permissible exposures (MPE) recommended by the American National Standards Institute (ANSI). Here, we propose a method based on deep learning in order to enhance the signal-to-noise ratio of deep structures in the brain tissue. The proposed method is evaluated in an in vivo sheep brain imaging experiment. We believe this method can facilitate clinical translation of photoacoustic technique in brain imaging, especially in neonates via transfontanelle imaging.

Citation Download Citation

Rayyan Manwar, Xin Li, Sadreddin Mahmoodkalayeh, Eishi Asano, Dongxiao Zhu, and Kamran Avanaki "Improved photoacoustic brain imaging using a deep learning protocol", Proc. SPIE 11642, Photons Plus Ultrasound: Imaging and Sensing 2021, 116423Q (11 March 2021); https://doi.org/10.1117/12.2581238

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