An intensity-based post-processing tool for 3D instance segmentation of organelles in soft X-ray tomograms.

ABSTRACT: Investigating the 3D structures and rearrangements of organelles within a single cell is critical for better characterizing cellular function. Imaging approaches such as soft X-ray tomography have been widely applied to reveal a complex subcellular organization involving multiple inter-organelle interactions. However, 3D segmentation of organelle instances has been challenging despite its importance in organelle characterization. Here we propose an intensity-based post-processing tool to identify and separate organelle instances. Our tool separates sphere-like (insulin vesicle) and columnar-shaped organelle instances (mitochondrion) based on the intensity of raw tomograms, semantic segmentation masks, and organelle morphology. We validate our tool using synthetic tomograms of organelles an

SUBMITTER: Li A 

PROVIDER: S-EPMC9436087 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature