1. Extraction of the Number of Peroxisomes in Yeast Cells by Automated Image Analysis
- Author
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John D. Aitchison, Olli Yli-Harja, Jyrki Selinummi, Ramsey A. Saleem, Antti Niemistö, and Ilya Shmulevich
- Subjects
education.field_of_study ,Microscopy, Confocal ,Saccharomyces cerevisiae ,Feature extraction ,Population ,Reproducibility of Results ,Image segmentation ,Biology ,Peroxisome ,Image Enhancement ,biology.organism_classification ,Sensitivity and Specificity ,Thresholding ,Yeast ,Pattern Recognition, Automated ,Cell biology ,Transformation (genetics) ,Imaging, Three-Dimensional ,Artificial Intelligence ,Image Interpretation, Computer-Assisted ,Peroxisomes ,education ,Algorithms - Abstract
An automated image analysis method for extract- ing 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 man- ually obtained results. Index Terms— Yeast, peroxisome biogenesis, image analysis, quantification, segmentation, watershed transformation
- Published
- 2006
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