Abstract:
Objective To investigate the potential of two step cluster ing analysis in patho logicalimage analysis.
Methods Two step clustering was used to cluster normal, low-grade squamous intraepithelial lesion, high-grade squamous intraepit helial lesion cervical cells with 51 char acters.Firstly, the cases were clustered intomany small sub-clusters and then the sub-clusters were clustered into the desired number of clusters.The number of clusters was automatically determined by Bayesian Information Criteria with log-likelihood distance measure.
Results Classification accuracy of normal, low-grade squamous intr aepithelial lesion and high-grade squamous intraepithelial lesion cervical cells was 98.0%, 96.1% and 100%, respectively.
Conclusion With the high classification accuracy, the two step clustering can measure the variables.significance, which could provide useful information for image analysis.