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Abstract #4964

Texture analysis of prostate MRI by using the Gray-Level Co-Occurrence Matrix (GLCM) for the characterization of prostate cancer, normal prostatic peripheral zone, and transition zone

Sung Kyoung Moon1, Hyug-Gi Kim2, Kyung Mi Lee1, and Joo Won Lim1

1Radiology, Kyung Hee University Hospital, College of Medicine, Kyung Hee University, Seoul, Korea, Republic of, 2Biomedical Engineering, College of Electronic Information Engineering, Kyung Hee University, Korea, Republic of

GLCM is a mathematical method that extracts the various quantitative parameters representing texture features of the images. Our hypothesis is that the texture analysis of prostate MRI can be an additional problem-solving tool in differentiating cancer and normal prostate tissue. The texture parameters of ROIs in prostate cancer, normal peripheral zone, and normal transitional zone in T2WI were extracted and compared statistically in 20 prostate cancer patients. The correlation, energy, and maximum probability in prostate cancer and peripheral zone are significantly different. The texture analysis can be used for the characterization and differentiation of prostate cancer and normal prostate tissue.

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