articleNature MethodsOct 17, 2022HYBRID OA

Omnipose: a high-precision morphology-independent solution for bacterial cell segmentation

KJKevin J. CutlerCSCarsen StringerTWTeresa W. LoLRLuca RappezNSNicholas Stroustrup

University of Washington · Janelia Research Campus · +4 more institutions

PubMed
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Abstract

Advances in microscopy hold great promise for allowing quantitative and precise measurement of morphological and molecular phenomena at the single-cell level in bacteria; however, the potential of this approach is ultimately limited by the availability of methods to faithfully segment cells independent of their morphological or optical characteristics. Here, we present Omnipose, a deep neural network image-segmentation algorithm. Unique network outputs such as the gradient of the distance field allow Omnipose to accurately segment cells on which current algorithms, including its predecessor, Cellpose, produce errors. We show that Omnipose achieves unprecedented segmentation performance on mixed bacterial…

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Topics & keywords

Topics
Keywords
  • Segmentation
  • Morphology (biology)
  • Artificial intelligence
  • Computer science
  • Biology
  • Biological system
  • Pattern recognition (psychology)
  • Microscopy
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