Cellstitch: 3D cellular anisotropic image segmentation via optimal transport.

ABSTRACT:

Background

Spatial mapping of transcriptional states provides valuable biological insights into cellular functions and interactions in the context of the tissue. Accurate 3D cell segmentation is a critical step in the analysis of this data towards understanding diseases and normal development in situ. Current approaches designed to automate 3D segmentation include stitching masks along one dimension, training a 3D neural network architecture from scratch, and reconstructing a 3D volume from 2D segmentations on all dimensions. However, the applicability of existing methods is hampered by inaccurate segmentations along the non-stitching dimensions, the lack of high-quality diverse 3D training data, and inhomogeneity of image resolution along orthogonal directions due to acquisition c

SUBMITTER: Liu Y 

PROVIDER: S-EPMC10724925 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature