The target of CBIR is to recover pertinent clinical pictures from the clinical information base concerning the question picture in a shorter range of time. All the proposed approaches are unique, yet the exploration objective is to accomplish better exactness in a sensible measure of time. The underlying period of this examination presents an element determination procedure that expects to ad lib the clinical picture finding by choosing unmistakable highlights. The second period of the examination separates highlights and the affiliation rules are framed by the proposed Classification Based on Highly Strong Association Rules (CHiSAR). At last, the standard subset classifier is utilized to order between the pictures. The last period of the examination removes the highlights from the kidney pictures and the affiliation rules are diminished for better execution. The picture significance surmising is performed lastly, double and the best first pursuit characterization is utilized to group between the pictures. The framework was viably ready for 10 classes of CT examine picture and in the proposed IICBMergeFS based CNN classifier give high precision of 97.24% is acquired by contrasting and the condition of expressions in MATLAB programming.