Protocol to train a support vector machine for the automatic curation of bacterial cell detections in microscopy images.

Journal: STAR protocols
Published Date:

Abstract

Manual curation of bacterial cell detections in microscopy images remains a time-consuming and laborious task. This work offers a comprehensive, step-by-step tutorial on training a support vector machine to autonomously distinguish between good and bad cell detections. Jupyter notebooks are included to perform feature extraction, labeling, and training of the machine learning model. This method can readily be incorporated into profiling pipelines aimed at extracting a multitude of features across large collections of individual cells, strains, and species. For complete details on the use and execution of this protocol, please refer to Govers et al..

Authors

  • Bart Steemans
    Department of Biology, KU Leuven, 3001 Leuven, Belgium.
  • Sander K Govers
    Department of Biology, KU Leuven, 3001 Leuven, Belgium. Electronic address: sander.govers@kuleuven.be.