Extraction of the number of peroxisomes in yeast cells by automated image analysis.
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.
Niemistö
Antti
A
Institute of Signal Processing, Tampere University of Technology, Finland.
Selinummi
Jyrki
J
Saleem
Ramsey
R
Shmulevich
Ilya
I
Aitchison
John
J
Yli-Harja
Olli
O
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