PostFocus: automated selective post-acquisition high-throughput focus restoration using diffusion model for label-free time-lapse microscopy.

ABSTRACT:

Motivation

High-throughput time-lapse imaging is a fundamental tool for efficient living cell profiling at single-cell resolution. Label-free phase-contrast video microscopy enables noninvasive, nontoxic, and long-term imaging. The tradeoff between speed and throughput, however, implies that despite the state-of-the-art autofocusing algorithms, out-of-focus cells are unavoidable due to the migratory nature of immune cells (velocities >10 μm/min). Here, we propose PostFocus to (i) identify out-of-focus images within time-lapse sequences with a classifier, and (ii) deploy a de-noising diffusion probabilistic model to yield reliable in-focus images.

Results

De-noising diffusion probabilistic model outperformed deep discriminative models with a superior performance on the whole

SUBMITTER: Wu KL 

PROVIDER: S-EPMC11520405 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature