title: Cell motility dynamics: a novel segmentation algorithm to quantify multi-cellular bright field microscopy images.
abstract: Confocal microscopy analysis of fluorescence and morphology is becoming the standard tool in cell biology and molecular imaging. Accurate quantification algorithms are required to enhance the understanding of different biological phenomena. We present a novel approach based on image-segmentation of multi-cellular regions in bright field images demonstrating enhanced quantitative analyses and better understanding of cell motility. We present MultiCellSeg, a segmentation algorithm to separate between multi-cellular and background regions for bright field images, which is based on classification of local patches within an image: a cascade of Support Vector Machines (SVMs) is applied using basic image features. Post processing includes additional classification and graph-cut segmentation to reclassify erroneous regions and refine the segmentation. This approach leads to a parameter-free and robust algorithm. Comparison to an alternative algorithm on wound healing assay images demonstrates its superiority. The proposed approach was used to evaluate common cell migration models such as wound healing and scatter assay. It was applied to quantify the acceleration effect of Hepatocyte growth factor/scatter factor (HGF/SF) on healing rate in a time lapse confocal microscopy wound healing assay and demonstrated that the healing rate is linear in both treated and untreated cells, and that HGF/SF accelerates the healing rate by approximately two-fold. A novel fully automated, accurate, zero-parameters method to classify and score scatter-assay images was developed and demonstrated that multi-cellular texture is an excellent descriptor to measure HGF/SF-induced cell scattering. We show that exploitation of textural information from differential interference contrast (DIC) images on the multi-cellular level can prove beneficial for the analyses of wound healing and scatter assays. The proposed approach is generic and can be used alone or alongside traditional fluorescence single-cell processing to perform objective, accurate quantitative analyses for various biological applications.
authors.affiliation: Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel.
authors.forename: Assaf
authors.initials: A
authors.lastname: Zaritsky
authors.forename: Sari
authors.initials: S
authors.lastname: Natan
authors.forename: Judith
authors.initials: J
authors.lastname: Horev
authors.forename: Inbal
authors.initials: I
authors.lastname: Hecht
authors.forename: Lior
authors.initials: L
authors.lastname: Wolf
authors.forename: Eshel
authors.initials: E
authors.lastname: Ben-Jacob
authors.forename: Ilan
authors.initials: I
authors.lastname: Tsarfaty
mesh_terms: D000465:Algorithms; D000818:Animals; D002460:Cell Line; D045744:Cell Line, Tumor; D002465:Cell Movement / Q000502:physiology*; D004285:Dogs; D007091:Image Processing, Computer-Assisted; D051379:Mice; D008853:Microscopy / Q000379:methods*; D018613:Microscopy, Confocal; D060388:Support Vector Machine
references.citation: Proc Natl Acad Sci U S A. 2007 Oct 9;104(41):15988-93
references.pmid: 17905871
references.citation: BMC Biotechnol. 2004 Sep 09;4:21
references.pmid: 15357872
references.citation: Biotechniques. 2009 Apr;46(4):265-74
references.pmid: 19450233
references.citation: Neuron. 2001 Apr;30(1):79-89
references.pmid: 11343646
references.citation: Int J Biochem Cell Biol. 1999 Dec;31(12):1357-62
references.pmid: 10641789
references.citation: Methods Mol Biol. 1999;96:177-82
references.pmid: 10098136
references.citation: Nat Rev Mol Cell Biol. 2003 Dec;4(12):915-25
references.pmid: 14685170
references.citation: Stud Health Technol Inform. 2003;95:164-9
references.pmid: 14663981
references.citation: Genome Biol. 2006;7(10):R100
references.pmid: 17076895
references.citation: Biotechniques. 2007 Jan;42(1):71-5
references.pmid: 17269487
references.citation: PLoS Comput Biol. 2010 Nov 24;6(11):e1000974
references.pmid: 21124870
references.citation: Cell Res. 2005 Jan;15(1):49-51
references.pmid: 15686627
references.citation: Cancer Res. 1990 Jan 15;50(2):227-34
references.pmid: 2136804
references.citation: Cytometry A. 2003 Feb;51(2):119-26
references.pmid: 12541286
references.citation: Med Eng Phys. 2012 Mar;34(2):225-32
references.pmid: 21820939
references.citation: Biophys J. 2010 May 19;98(9):1790-800
references.pmid: 20441742
references.citation: Cytometry A. 2011 Mar;79(3):227-32
references.pmid: 22045642
references.citation: Cell Motil Cytoskeleton. 1997;37(1):33-43
references.pmid: 9142437
references.citation: Nat Methods. 2009 Sep;6(9):667-72
references.pmid: 19684595
references.citation: Photodermatol Photoimmunol Photomed. 2009 Apr;25(2):75-80
references.pmid: 19292782
references.citation: BMC Bioinformatics. 2009 Mar 03;10:75
references.pmid: 19257905
references.citation: BMC Cell Biol. 2005 Mar 03;6(1):9
references.pmid: 15743539
references.citation: Mol Biol Cell. 2000 Aug;11(8):2565-75
references.pmid: 10930454
references.citation: PLoS One. 2009 Oct 22;4(10):e7497
references.pmid: 19847301
references.citation: EMBO J. 2006 Aug 9;25(15):3534-45
references.pmid: 16858414