Liver cancer is most recently referred and researched medical data as it is considered to be the largest organ with monopolistic characters and features. Liver clustering and Pattern detection is discussed in this paper with narrow down application design for contour shape detection and analysis. The research article is discussed with 30 clinical datasets for standardization in research outcomes and analysis. Under this research functionality attributes such as PSNR, Entropy, Cross Correlation, and Mutual Information and Structural Similarity Index (SSIM) are computed and compared with respect to the trivial techniques. An observatory analysis is archived in the results and outcome. The proposed technique achieves 90% of matching score under noisy environment of processing under contamination varying between 10 to 30 dB. The PSNR comparison ratio is highly influenced with an improved reduction range of 40%, MI and SSIM are exponentially decreased from 10% onwards to 30 and 40% respectively from the original.
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