High-resolution lensless holographic microscopy using a physics-aware deep network.

ABSTRACT:

Significance

Lensless digital inline holographic microscopy (LDIHM) is an emerging quantitative phase imaging modality that uses advanced computational methods for phase retrieval from the interference pattern. The existing end-to-end deep networks require a large training dataset with sufficient diversity to achieve high-fidelity hologram reconstruction. To mitigate this data requirement problem, physics-aware deep networks integrate the physics of holography in the loss function to reconstruct complex objects without needing prior training. However, the data fidelity term measures the data consistency with a single low-resolution hologram without any external regularization, which results in a low performance on complex biological data.

Aim

We aim to mitigate the challenge

SUBMITTER: Galande AS 

PROVIDER: S-EPMC11460617 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature