Building cell models and simulations from microscope images

Methods. 2016 Mar 1:96:33-39. doi: 10.1016/j.ymeth.2015.10.011. Epub 2015 Oct 17.

Abstract

The use of fluorescence microscopy has undergone a major revolution over the past twenty years, both with the development of dramatic new technologies and with the widespread adoption of image analysis and machine learning methods. Many open source software tools provide the ability to use these methods in a wide range of studies, and many molecular and cellular phenotypes can now be automatically distinguished. This article presents the next major challenge in microscopy automation, the creation of accurate models of cell organization directly from images, and reviews the progress that has been made towards this challenge.

Keywords: Cell organization; Cell shape; Computational biology; Generative models; Image-based modeling.

Publication types

  • Research Support, N.I.H., Extramural
  • Review

MeSH terms

  • Cell Shape
  • Computational Biology / instrumentation
  • Computational Biology / methods
  • Computer Simulation
  • HeLa Cells
  • Humans
  • Image Processing, Computer-Assisted*
  • Machine Learning*
  • Microscopy, Fluorescence / methods
  • Microscopy, Fluorescence / statistics & numerical data*
  • Models, Biological*
  • Pattern Recognition, Automated*
  • Software