Automatic cell detection in phase-contrast images for evaluation of electroporation efficiency in vitro

In the research of electroporation, we often need to know the percent of electroporated cells under different experimental conditions. Manual counting of the cells in digital images is time-consuming and subjective, especially on phase contrast images. In this paper, we present an automatic cell counting method based on optimization of ITCN (Image-based Tool for Counting Nuclei) algorithm’s parameters to fit training data that is based on counts from user or expert. In comparing the results of automatic cell counting and user manual counting 94,21 % average agreement was achieved what is good.

[1]  Jon Wakefield,et al.  The automated counting of spots for the ELISpot assay. , 2006, Journal of immunological methods.

[2]  Kenong Wu,et al.  Live cell image segmentation , 1995, IEEE Transactions on Biomedical Engineering.

[3]  J. D. Johnson,et al.  An automatic cell counting method for optical images , 1999, Proceedings of the First Joint BMES/EMBS Conference. 1999 IEEE Engineering in Medicine and Biology 21st Annual Conference and the 1999 Annual Fall Meeting of the Biomedical Engineering Society (Cat. N.

[4]  B. S. Manjunath,et al.  Automated tool for the detection of cell nuclei in digital microscopic images: application to retinal images. , 2006, Molecular vision.

[5]  M Cemazar,et al.  Improvement of combined modality therapy with cisplatin and radiation using electroporation of tumors. , 2000, International journal of radiation oncology, biology, physics.

[6]  N. Pavselj,et al.  DNA electrotransfer into the skin using a combination of one high- and one low-voltage pulse. , 2005, Journal of controlled release : official journal of the Controlled Release Society.

[7]  D Miklavcic,et al.  Evaluation of cell membrane electropermeabilization by means of a nonpermeant cytotoxic agent. , 2000, BioTechniques.

[8]  Marie-Pierre Rols,et al.  Electropermeabilization, a physical method for the delivery of therapeutic molecules into cells. , 2006, Biochimica et biophysica acta.

[9]  M. Torres-Cisneros,et al.  Detection of Biological Cells in Phase-Contrast Microscopy Images , 2006, 2006 Fifth Mexican International Conference on Artificial Intelligence.