A deep learning model based on hybrid convolutional and recurrent neural networks is proposed for generating sequential optoacoustic, unmixed optoacoustic of a specific contrast agent, and ultrasound images in order to extend the stack of crosssectional images and reduce acquisition time by approximately 71%.
For further details please visit the article by Aniwat Juhong, Bo Li, Yifan Liu, Cheng-You Yao, Chia-Wei Yang, Dalen W. Agnew, Yu Leo Lei, Gary D. Luker, Harvey Bumpers, Xuefei Huang, Wibool Piyawattanametha, and Zhen Qiu (e202300142).

This study explored the feasibility of diffuse reflectance spectroscopy (DRS) for discrimination between brain cancer and noncancer tissues. Our method could achieve a sensitivity of 93% and specificity of 95% for discriminating high-grade glioma from normal white matter. Our results showed that DRS has the potential to be used for label-free, real-time in vivo cancer detection during brain surgery.
For further details please visit the article by Kerui Li, Qijia Wu, Shiyu Feng, Hongyou Zhao, Wei Jin, Haixia Qiu, Ying Gu, and Defu Chen (e202300195).

A method based on deep learning was proposed to enhance the defocused resolution and signal-to-noise ratio of optical-resolution photoacoustic microscopy. A fully dense U-Net was trained with randomly distributed sources of different shapes to improve the quality of photoacoustic images. The results show that the PSNR of defocused signal was enhanced by more than 1.2 times. An over 2.6-fold enhancement in lateral resolution and an over 3.4-fold enhancement in axial resolution of defocused regions were achieved.
For further details please visit the article by Rui Wang, Zhipeng Zhang, Ruiyi Chen, Xiaohai Yu, Hongyu Zhang, Gang Hu, Qiegen Liu, Xianlin Song (e202300149).

Cells expressing firefly luciferase that were labelled with gold nanorods (GNRs) could be visualised with multispectral optoacoustic tomography (MSOT), whereas control cells did not generate an MSOT signal. The white line in the left image indicates the imaging plain in MSOT. By combining these two imaging modalities, we obtain information about cell viability (bioluminescence) whereas MSOT shows the precise location of the cells.
For further details please visit the article by Alejandra Hernandez Pichardo, James Littlewood, Arthur Taylor, Bettina Wilm, Raphaël Lévy, and Patricia Murray (e202300109).