SAMCell: Generalized label-free biological cell segmentation with segment anything.

ABSTRACT:

Background

When analyzing cells in culture, assessing cell morphology (shape), confluency (density), and growth patterns are necessary for understanding cell health. These parameters are generally obtained by a skilled biologist inspecting light microscope images, but this can become very laborious for high-throughput applications. One way to speed up this process is by automating cell segmentation. Cell segmentation is the task of drawing a separate boundary around each cell in a microscope image. This task is made difficult by vague cell boundaries and the transparent nature of cells. Many techniques for automatic cell segmentation exist, but these methods often require annotated datasets, model retraining, and associated technical expertise.

Results

We present SAMCell, a

SUBMITTER: VandeLoo AD 

PROVIDER: S-EPMC12416835 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature