title: Extraction of the number of peroxisomes in yeast cells by automated image analysis.
abstract: An automated image analysis method for extracting the number of peroxisomes in yeast cells is presented. Two images of the cell population are required for the method: a bright field microscope image from which the yeast cells are detected and the respective fluorescent image from which the number of peroxisomes in each cell is found. The segmentation of the cells is based on clustering the local mean-variance space. The watershed transformation is thereafter employed to separate cells that are clustered together. The peroxisomes are detected by thresholding the fluorescent image. The method is tested with several images of a budding yeast Saccharomyces cerevisiae population, and the results are compared with manually obtained results.
authors.affiliation: Institute of Signal Processing, Tampere University of Technology, Finland.
authors.forename: Antti
authors.initials: A
authors.lastname: Niemistö
authors.forename: Jyrki
authors.initials: J
authors.lastname: Selinummi
authors.forename: Ramsey
authors.initials: R
authors.lastname: Saleem
authors.forename: Ilya
authors.initials: I
authors.lastname: Shmulevich
authors.forename: John
authors.initials: J
authors.lastname: Aitchison
authors.forename: Olli
authors.initials: O
authors.lastname: Yli-Harja
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D018613:Microscopy, Confocal / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D020675:Peroxisomes / Q000648:ultrastructure*; D015203:Reproducibility of Results; D012441:Saccharomyces cerevisiae / Q000166:cytology*; D012680:Sensitivity and Specificity