Creating a universal cell segmentation algorithm

Cell segmentation currently involves the use of various bespoke algorithms designed for specific cell types, tissues, staining methods and microscopy technologies. We present a universal algorithm that can segment all kinds of microscopy images and cell types across diverse imaging protocols.

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Bibliographic Details
Published inNature methods Vol. 21; no. 6; pp. 950 - 951
Format Journal Article
LanguageEnglish
Published New York Nature Publishing Group US 01.06.2024
Nature Publishing Group
Subjects
631/114/1305
631/114/1564
Algorithms
Animals
Artificial intelligence
Bioinformatics
Biological Microscopy
Biological research
Biological Techniques
Biomedical and Life Sciences
Biomedical Engineering/Biotechnology
Collaboration
Datasets
Deep learning
Efficiency
Humans
Image Processing, Computer-Assisted - methods
Laboratories
Life Sciences
Machine learning
Medical research
Microscopy
Proteomics
Research Briefing
Segmentation
Software
Online AccessGet full text
ISSN1548-7091
1548-7105
1548-7105
DOI10.1038/s41592-024-02254-1

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Summary:Cell segmentation currently involves the use of various bespoke algorithms designed for specific cell types, tissues, staining methods and microscopy technologies. We present a universal algorithm that can segment all kinds of microscopy images and cell types across diverse imaging protocols.
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ISSN:1548-7091
1548-7105
1548-7105
DOI:10.1038/s41592-024-02254-1