Physics-informed learning in Computational Imaging for Biomedical Optical Imaging


2020-12-28 11:14:44 208

Computational Imaging, balancing image formation and information extraction between the physical and computational domains, brings distinctively new insights into biomedical optical imaging, such as digital holographic microscopy. However, the imaging depth is still limited, and imaging through scattering media with decent spatial and temporal resolution remains a big challenge. We are devoted to developing physics-informed deep learning reconstruction methods to restore the target visual information for digital holographic, which greatly overcome the physical limits of optics. We will also explore the frontiers of computing imaging technology in multi-dimensional and multi-scale imaging for 3D pathology and live-cell applications. Computational imaging will extend the frontiers in our observation abilities and decrease the cost of various high-performance imaging setups, contributing significantly to the biomedical optical imaging field.