Abstract
Transitional Bladder cell carcinoma is one of the most common cancers of the urinary tract, accounting for approximately 90% of Bladder cancers. In this research a new computer-based system "Design of a Hybrid Intelligent System for Transitional Bladder Cell Carcinoma Diagnosis" (DHSTCCD) has been proposed and implemented. The proposed system is composed of two main phases, the first phase is the "cell analysis phase" which consists of three main stages including segmentation stage using "Genetic Optimization Based Fuzzy Image Segmentation Algorithm" (GOFISA), morphometric and photometric feature extraction stage and "Neuro-Fuzzy Classifier Model" (NFCM) stage that has been developed and implemented to classify a set of normal and abnormal cells using hybrid intelligent technique that combines the artificial neural network and fuzzy logic.
The second phase is the "patient data analysis phase", in this phase a rule-based Fuzzy Expert System has been proposed and implemented that uses the laboratory and clinical data and simulates an expert doctor’s behavior. The final diagnosis of the patients is determined from the results of the fuzzy expert system and the NFCM.
