Back to search

Article

SAMCell: Generalized Label-Free Biological Cell Segmentation with Segment Anything

2025-02-08

Abstract excerpt

<h4>Background</h4> 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...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
e587db56-30d8-5717-8500-194c5d0ff9cc
DOI
10.1101/2025.02.06.636835
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
SAMCell: Generalized Label-Free Biological Cell Segmentation with Segment AnythingDOI 10.1101/2025.02.06.636835
Select a neighboring publication to make it the new centre.