title: In-vitro cell quantification method based on depth dependent analysis of brain tissue microscopic images.
abstract: In this study we developed a new automatic quantification method to count the number of targeted fluorescently labeled molecules of in-vitro rat brain tissue images. NG2+ glial cells were monitored in order to detect their proliferation to their same kind of cells or to another astrocyte cells using different fluorescently labeled molecules. The method is based on morphological segmentation followed by depth-dependent detection operation applied to a stack of confocal microscopic images. The number of local maxima peak points was used to count the number of the labeled cells. The method shows good promise for the computer-aided assessment in neurological studies for accurate automatic counting systems.
authors.affiliation: Cellular Function Imaging Laboratory, RIKEN Center for Molecular Imaging Science, Kobe, Japan. mustafa@riken.jp
authors.forename: Mustafa M
authors.initials: MM
authors.lastname: Sami
authors.forename: Yasuhisa
authors.initials: Y
authors.lastname: Tamura
authors.forename: Cui
authors.initials: C
authors.lastname: Yilong
authors.forename: Hisakazu
authors.initials: H
authors.lastname: Kikuchi
authors.forename: Yosky
authors.initials: Y
authors.lastname: Kataoka
mesh_terms: D000818:Animals; D002452:Cell Count / Q000379:methods*; D002460:Cell Line; D049109:Cell Proliferation; D058948:Cell Tracking / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008297:Male; D018613:Microscopy, Confocal / Q000379:methods*; D009457:Neuroglia / Q000166:cytology* / Q000502:physiology; D010363:Pattern Recognition, Automated / Q000379:methods*; D051381:Rats; D017208:Rats, Wistar; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique