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A novel approach to automated cell counting for studying human corneal epithelial cells
- Source :
- EMBC
- Publication Year :
- 2011
- Publisher :
- IEEE, 2011.
-
Abstract
- A novel automated cell counting technique for cell sample images used to study the side-effects of lens cleaning solutions on human corneal epithelial cells is developed. The proposed multi-step approach integrates non-maximum suppression, seeded region growing, connected component analysis, and adaptive thresholding to produce segmentation and classification results that are robust to background illumination variation and clustering of cells. The proposed algorithm is computationally efficient, and experimental results show that the average detection rate of nucleated cells is greater than 90% with the proposed technique as opposed to the state-of-the-art level set method which gives an accuracy of less than 65%.
- Subjects :
- Level set method
Computer science
Cell Count
Dermoscopy
Sensitivity and Specificity
Pattern Recognition, Automated
Nucleated cell
Image Interpretation, Computer-Assisted
Humans
Segmentation
Computer vision
Cluster analysis
Microscopy
Contextual image classification
business.industry
Epithelium, Corneal
Reproducibility of Results
Epithelial Cells
Image segmentation
Image Enhancement
Thresholding
Cell Tracking
Region growing
Artificial intelligence
business
Connected-component labeling
Algorithms
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society
- Accession number :
- edsair.doi.dedup.....5b6765d7cdde347747f52fb2c3a26e39