Whole tissue imaging of cellular boundaries at sub-micron resolutions for deep learning cell segmentation: Applications in the analysis of epithelial bending of ectoderm.

ABSTRACT:

Background

To understand cellular morphology, biologists have relied on traditional optical microscopy of tissues combined with tissue clearing protocols to image structures deep within tissues. Unfortunately, these protocols often struggle to retain cell boundary markers, especially at high enough resolutions necessary for precise cell segmentation. This limitation affects the ability to study changes in cell shape during major developmental events.

Results

We introduce a method that preserves cell boundary markers and matches the refractive index of tissues with water. This technique enables the use of high-magnification, long working distance water-dipping objectives that provide sub-micron resolution images. We subsequently segment individual cells using a trained neural

SUBMITTER: Norris SCP 

PROVIDER: S-EPMC12818342 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature