title: Quantification of vesicles in differentiating human SH-SY5Y neuroblastoma cells by automated image analysis.
abstract: A new automated image analysis method for quantification of fluorescent dots is presented. This method facilitates counting the number of fluorescent puncta in specific locations of individual cells and also enables estimation of the number of cells by detecting the labeled nuclei. The method is here used for counting the AM1-43 labeled fluorescent puncta in human SH-SY5Y neuroblastoma cells induced to differentiate with all-trans retinoic acid (RA), and further stimulated with high potassium (K+) containing solution. The automated quantification results correlate well with the results obtained manually through visual inspection. The manual method has the disadvantage of being slow, labor-intensive, and subjective, and the results may not be reproducible even in the intra-observer case. The automated method, however, has the advantage of allowing fast quantification with explicitly defined methods, with no user intervention. This ensures objectivity of the quantification. In addition to the number of fluorescent dots, further development of the method allows its use for quantification of several other parameters, such as intensity, size, and shape of the puncta, that are difficult to quantify manually.
authors.affiliation: Institute of Signal Processing, Tampere University of Technology, FIN-33101 Tampere, Finland. jyrki.selinummi@tut.fi
authors.forename: Jyrki
authors.initials: J
authors.lastname: Selinummi
authors.forename: Jertta-Riina
authors.initials: JR
authors.lastname: Sarkanen
authors.forename: Antti
authors.initials: A
authors.lastname: Niemistö
authors.forename: Marja-Leena
authors.initials: ML
authors.lastname: Linne
authors.forename: Timo
authors.initials: T
authors.lastname: Ylikomi
authors.forename: Olli
authors.initials: O
authors.lastname: Yli-Harja
authors.forename: Tuula O
authors.initials: TO
authors.lastname: Jalonen
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D002454:Cell Differentiation; D045744:Cell Line, Tumor; D002471:Cell Transformation, Neoplastic / Q000473:pathology*; D017143:Fuzzy Logic; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008856:Microscopy, Fluorescence / Q000379:methods*; D009447:Neuroblastoma / Q000473:pathology*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D022161:Transport Vesicles / Q000473:pathology*