The nature of statistical learning theory
The nature of statistical learning theory
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This paper presents an automatic system for morphological screening of the bladder cells. This system is intended to increase efficiency of the subsequent fluorescence in situ hybridization examination by limiting the number of suspicious cells. The system works in two major phases. The first phase is slide scanning. The second stage includes cells detection and morphological analysis. Both stages refine their results using supervised classification algorithm. The developed method was tested on nine microscopical slides, containing more than 12000 manually labeled cells. The results provided by the system were compared to the ground truth labeled by a human expert.