eng Oriental Scientific Publishing Company Biomedical and Pharmacology Journal 0974-6242 2019-06-25 12 2 1015 1021 10.13005/bpj/1730 27750 article S. M. Vijaya 1 K. Suresh 2 RRCE, Bengaluru, 560074 - India. College of Engineering and Technology, Bengaluru, 560049 - India. Robotic guided medical system requires efficient mechanism of compression of Region of Diagnostics Interest (RODI) in medical images to overcome the tradeoff among efficiency and time which is a computationally challenging task. This task involves the requirement of suitable noise filtering, segmentation, critical feature selection especially at corners of RODI and encoding process. This paper proposes a framework namely ICRODI to evaluate a hybrid approach of compression for region of diagnostic interest in Brain MRI as well as for rest of the region. The approaches used are median filter, thresholding as pre-processing and fuzzy c-mean clustering, Harris corner detection, s-shape fuzzy for segmentation and feature point selection optimization. Further alpha hull of the convex hull is used for getting the volume of the mass and finally the wavelet co-efficient based compression is applied. The effectiveness of the proposed ICRODI is validated by evaluating MSE and PSNR for both RODI and Non-ROSI. The average value of the PSRN for RODI is found approximately 49 % higher as compared to the non-RODI and MSE of the RODI is reduced by approximately 33% as compared to the non-RODI after simulating the process on a numerical simulation platform. The achieved results are quite promising and could be optimized for the VLSI implementation in future. https://biomedpharmajournal.org/vol12no2/icrodi-image-compression-of-region-of-diagnostics-interest-rodi-using-layer-segmentation-and-wavelet/ Brain MRI Image Coding Medical Image Processing Medical Robotics Region of Interest Compression