• Dr P.Sreenivasulu
• N.Jaswanthsai
• A.Sundeep Kumar
• G.Penchala Nitheesh
• P.srikanth

This paper offers a medical images, namely segmentation (modified region growing (MRG) algorithm), image compression (ROI-discrete cosine transform (DCT) and SPHIT encoding methods, non-ROI-discrete wavelet transform (DWT) and merge-based Huffman encoding (MHE)). Subsequently, the filter coefficients of both the DCT and DWT are optimized using improvised steering angle and gear-basedGray wolf optimization algorithm. Finally, decompression stage takes place by adopting the reverse process of compression with similar optimized coefficients. Here, the filter coefficients are tuned in such a way that the CR has to be minimal. In addition, an algorithmic analysis is carried out for the proposed model and the outcomes are discussed. In the final step, decompression is done by implementing the reverse concept of compression process with similar optimized coefficients. The filter coefficients are tuned in such a way that the Compression Ratio (CR) should be maximum In addition, the comparative analysis over the state-of-the-art models proves the superior performance of the proposed model.

"Medical Image Compression Using Gray Wolf Optimization Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.d460-d466, May-2023, Available :http://www.jetir.org/papers/JETIR2305364.pdf

"Medical Image Compression Using Gray Wolf Optimization Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. ppd460-d466, May-2023, Available at : http://www.jetir.org/papers/JETIR2305364.pdf