Vahid Anari - Islamic Azad University Khoramabad Branch
Rasoul Amirfattahi - Digital Signal Processing Research Lab., Department of Electrical and Computer Engineering, Isfehan
Parvin Mahzouni - Isfehan University of Medical Science, Isfahan, Iran

Immuonohistochemically images of meningioma which are stained by ki66 marker contain positive and negative cells. Accurate counting the number of positive and negative cells in such images play a critical role in diagnosing diffrent type of meningioma cancer. Since pathological images of meningioma contain complex cell cluster accurate cell counting methodology is a major challenge for pathologist physicians. In this paper we provide a computer aided algorithm for detecting proliferative cells and mitosis index in immunohistochemically images of meningioma. In the first stage of the algorithm fuzzy c-means clustering was used to extract positive and negative cells based on CIElab color space. In the second stage, ultraerosion operation was applied to count the number of individual and overlapped cells. Experimental result show that the proposed algorithm is able to overcome some disadvantage of traditional approaches with acceptable accuracy by pathologist physicians.

Cell counting, Color segmentation, CIElabcolor space, Fuzzy c-means, Immunohistochemistry,Meningioma, Mitosis index, Ultra erosion