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Extraction of the Number of Peroxisomes in Yeast Cells by Automated Image Analysis
- Source :
- EMBC, Scopus-Elsevier
- Publication Year :
- 2006
- Publisher :
- IEEE, 2006.
-
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
- 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
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2006 International Conference of the IEEE Engineering in Medicine and Biology Society
- Accession number :
- edsair.doi.dedup.....fa845f0ebb8bc56360b80aafd234f2a1
- Full Text :
- https://doi.org/10.1109/iembs.2006.259890