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In this paper, the classification of liver diseases using first-order statistics (FOS) is implemented for automatic preliminary diagnosis of liver diseases. Region of interest (ROI) extracted from MRI images are used as the input to characterize different tissue, namely liver cyst, fatty liver and healthy liver using first-order statistics. The results for first-order statistics are given and their potential applicability in grid computing is discussed. The measurements extracted from First-order statistic include entropy and correlation achieved obvious classification range in detecting different tissues in this work.