Nowadays prostate disease is very common in adult and elderly men. Since all types of prostate diseases are having similar symptoms, it is difficult to diagnose malignant prostate at an early stage. In this work an attempt is made to identify the types of prostate diseases abdomen CT images of the patients using texture analysis. Prostate region is segmented the CT image slice. Texture features are extracted the segmented images using an evolving transform named Sequency based Mapped Real Transform (SMRT). Six different SMRT feature sets are derived by varying sub image size and block size. Each feature set is optimized using Genetic Algorithm (GA).

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