PHYSICS/PHYSIOLOGY-GUIDED QUANTITATIVE IMAGING
Development of physics- and physiology-based models to complement our instrument development for quantitative functional, metabolic, and molecular imaging at the microscopic level.
- N. Sun, A.C. Bruce, B. Ning, R. Cao, Y. Wang, F. Zhong, S.M. Peirce, and S. Hu, “Photoacoustic Microscopy of Vascular Adaptation and Tissue Oxygen Metabolism during Cutaneous Wound Healing,” Biomedical Optics Express, 13, no. 5 (2022):2695-2706. (Editor’s pick) https://doi.org/10.1364/BOE.456198
- N. Sun, B. Ning, A. Bruce, R. Cao, S. Seaman, T. Wang, R. Fritsche-Danielson, L. Carlsson, S. Peirce, S. Hu, “In vivo imaging of hemodynamic redistribution and arteriogenesis across a microvascular network,” Microcirculation, e12598 (2020). (Featured on cover) https://doi.org/10.1111/micc.12598
MACHINE LEARNING-ENABLED HIGH-PERFORMANCE IMAGING
Harnessing the power of advanced machine learning techniques to break through critical barriers associated with our cutting-edge imaging techniques.
- Y. Zhou, N. Sun, and S. Hu, “Deep Learning-powered Bessel-beam Multi-parametric Photoacoustic Microscopy,” IEEE Transactions on Medical Imaging (early access online). https://doi.org/10.1109/tmi.2022.3188739
- Z. Wang, Y. Zhou, and S. Hu, “Sparse Coding-enabled Low-fluence Multi-parametric Photoacoustic Microscopy,” IEEE Transactions on Medical Imaging 41, no. 4 (2021): 805-814. doi: 10.1109/TMI.2021.3124124
- SG. Sathyanarayana†, Z. Wang†, N. Sun, B. Ning, S. Hu*, JA. Hossack*, “Recovery of Blood Flow From Undersampled Photoacoustic Microscopy Data Using Sparse Modeling,” IEEE Transactions on Medical Imaging 41, no. 1 (2021): 103-120. (*corresponding author; †equal contribution).
- SG. Sathyanarayana, B. Ning, R. Cao, S. Hu, JA. Hossack. “Dictionary learning-based reverberation removal enables depth-resolved photoacoustic microscopy of cortical microvasculature in the mouse brain,” Scientific Reports, 8, 985 (2018). https://doi.org/10.1038/s41598-017-18860-3