Staining independent Bayes classifier for automated cell pattern recognition
Xinhua Zhuang, James Rafferty Lee, Yan Huang, Alan C. Nelson · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1993
Designing the optimal Bayes classifier for automated cell pattern recognition faces two major difficulties: (1) modeling and learning the conditional probabilities P(cell features--cell type) (2) developing staining independent strategies to handle staining dependent cell features while learning those conditional probabilities. In this paper, we will show such modeling and learning techniques as well as staining independent strategies. The result of the strategies tested on an automated system designed for cervical smear screening will also be reported.