Leveraging spatial-angular redundancy for self-supervised denoising of 3D fluorescence imaging without temporal dependency.

ABSTRACT: Photon noise is one of the fundamental limits in fluorescence imaging. Despite broad applications, existing self-supervised denoising methods rely on either temporal redundancy or spatial redundancy, leading to degradation in either temporal resolution or spatial resolution, especially for 3D imaging. Here, we propose light field denoising (LF-denoising), a self-supervised transformer framework leveraging spatial-angular redundancy based on the high-dimensional light field measurements to achieve high-fidelity denoising without relying on temporal information and avoiding associated artefacts in spatial domain. We demonstrate the advantage of LF-denoising over previous methods in highly dynamic 3D imaging with both simulations and experimental data across different species. Combined with s

SUBMITTER: Lu Z 

PROVIDER: S-EPMC12749375 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature