Synthetic Micrographs of Bacteria (SyMBac) allows accurate segmentation of bacterial cells using deep neural networks.

Journal: BMC biology
Published Date:

Abstract

BACKGROUND: Deep-learning-based image segmentation models are required for accurate processing of high-throughput timelapse imaging data of bacterial cells. However, the performance of any such model strictly depends on the quality and quantity of training data, which is difficult to generate for bacterial cell images. Here, we present a novel method of bacterial image segmentation using machine learning models trained with Synthetic Micrographs of Bacteria (SyMBac).

Authors

  • Georgeos Hardo
    Department of Engineering, University of Cambridge, Trumpington Street, Cambridge, UK.
  • Maximilian Noka
    Department of Engineering, University of Cambridge, Trumpington Street, Cambridge, UK.
  • Somenath Bakshi
    Department of Engineering, University of Cambridge, Trumpington Street, Cambridge, UK. sb2330@cam.ac.uk.