Real-time and universal network for volumetric imaging from microscale to macroscale at high resolution.

ABSTRACT: Light-field imaging has wide applications in various domains, including microscale life science imaging, mesoscale neuroimaging, and macroscale fluid dynamics imaging. The development of deep learning-based reconstruction methods has greatly facilitated high-resolution light-field image processing, however, current deep learning-based light-field reconstruction methods have predominantly concentrated on the microscale. Considering the multiscale imaging capacity of light-field technique, a network that can work over variant scales of light-field image reconstruction will significantly benefit the development of volumetric imaging. Unfortunately, to our knowledge, no one has reported a universal high-resolution light-field image reconstruction algorithm that is compatible with microscale, m

SUBMITTER: Lin B 

PROVIDER: S-EPMC12041240 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature