Image analysis for automatic segmentation of cytoplasms and classification of Rac1 activation
Version of Record online: 23 DEC 2003
Copyright © 2004 Wiley-Liss, Inc.
Cytometry Part A
Volume 57A, Issue 1, pages 22–33, January 2004
How to Cite
Lindblad, J., Wählby, C., Bengtsson, E. and Zaltsman, A. (2004), Image analysis for automatic segmentation of cytoplasms and classification of Rac1 activation. Cytometry, 57A: 22–33. doi: 10.1002/cyto.a.10107
- Issue online: 23 DEC 2003
- Version of Record online: 23 DEC 2003
- Manuscript Accepted: 30 SEP 2003
- Manuscript Revised: 2 SEP 2003
- Manuscript Received: 29 JAN 2003
- Amersham Biosciences, Cardiff, U.K.
- Swedish Foundation for Strategic Research
- Visual Information Technology program
- automatic image analysis;
- cytoplasm segmentation;
- intracellular translocation;
Rac1 is a GTP-binding molecule involved in a wide range of cellular processes. Using digital image analysis, agonist-induced translocation of green fluorescent protein (GFP) Rac1 to the cellular membrane can be estimated quantitatively for individual cells.
A fully automatic image analysis method for cell segmentation, feature extraction, and classification of cells according to their activation, i.e., GFP-Rac1 translocation and ruffle formation at stimuli, is described. Based on training data produced by visual annotation of four image series, a statistical classifier was created.
The results of the automatic classification were compared with results from visual inspection of the same time sequences. The automatic classification differed from the visual classification at about the same level as visual classifications performed by two different skilled professionals differed from each other. Classification of a second image set, consisting of seven image series with different concentrations of agonist, showed that the classifier could detect an increased proportion of activated cells at increased agonist concentration.
Intracellular activities, such as ruffle formation, can be quantified by fully automatic image analysis, with an accuracy comparable to that achieved by visual inspection. This analysis can be done at a speed of hundreds of cells per second and without the subjectivity introduced by manual judgments. Cytometry Part A 57A:22–33, 2004. © 2003 Wiley-Liss, Inc.