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PROAFTN: a fuzzy assignment method to grade bladder cancer malignancy using features generated by computer-assisted image analysis

Belacel N., Boulassel M.-R.

Foundations of Computing and Decision Sciences

2000

Vol. 25, No. 1

37-47

We recently developed a new fuzzy classification method named PROAFTN, which uses the multicriteria decision aid approach. The aim of this paper is to evaluate the performance of the proposed method to grade bladder cancer malignancy. For this purpose, 292 cases of bladder tumors, classified according to the old World Health Organization classification by a pathologist on three subjective levels of malignancy (137 low grade, 124 intermediate grade and 31 high grade) were tested using the 10-fold cross-validation technique. The features were generated by means of computer assisted microscope analysis of cell images and submitted to the PROAFTN method which determines the membership degrees of each case in each grade. In order to determine the accuracy of the classification, results obtained by the method were compared to the subjective grading made by the pathologist. The PROAFTN method yielded good results in terms of discrimination between low and high grades, while it was unable to provide a satisfying discrimination within the heterogeneous intermediate grade II group. These results seem to be in agreement with the literature concerning the clinical heterogeneity of the intermediate grade. From these results, it will be essential in the future to see whether any combination of other sets of features, such as clinical data, can better discriminate between the grades.