Observing biological spatio-angular structures and dynamics with statistical image reconstruction and polarized fluorescence microscopy.

ABSTRACT: Understanding molecular orientation and density distributions is essential for exploring biological structure and function. Polarized fluorescence microscopy (PFM) provides insights into molecular architecture but struggles to resolve three-dimensional (3D) molecular orientation distributions, particularly in densely labeled or structurally complex specimens. To address this, we introduce the efficient generalized Richardson-Lucy (eGRL) algorithm, a robust framework for reconstructing 3D molecular density and orientation (spatio-angular) distributions from PFM data. By modeling the imaging process in spatio-angular hyperspace, we propose a maximum-likelihood solution enhanced by dimensionality reduction and angular domain transformation to overcome computational challenges. eGRL improves a

SUBMITTER: Liu J 

PROVIDER: S-EPMC12754719 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature