Liver Tumor Detection Using Texture PCA of CT Images 


Vol. 13,  No. 6, pp. 601-606, Dec.  2006
10.3745/KIPSTB.2006.13.6.601


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  Abstract

The image data amount that used in medical institution with great development of medical technology is increasing rapidly. Therefore, people need automation method that use image processing description than macrography of doctors for analysis many medical image. In this paper, we propose that acquire texture information to using GLCM about liver area of abdomen CT image, and automatically detects liver tumor using PCA from this data. Method by one feature as intensity of existent liver tumor detection was most but we changed into 4 principal component accumulation images using GLCM's texture information 8 feature. Experiment result, 4 principal component accumulation image's variance percentage is 89.9%. It was seen this compare with liver tumor detecting that use only intensity about 92%. This means that can detect liver tumor even if reduce from dimension of image data to 4 dimensions that is the half in 8 dimensions.

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[IEEE Style]

H. S. Sur, M. Y. Chong, C. W. Lee, "Liver Tumor Detection Using Texture PCA of CT Images," The KIPS Transactions:PartB , vol. 13, no. 6, pp. 601-606, 2006. DOI: 10.3745/KIPSTB.2006.13.6.601.

[ACM Style]

Hyung Soo Sur, Min Young Chong, and Chil Woo Lee. 2006. Liver Tumor Detection Using Texture PCA of CT Images. The KIPS Transactions:PartB , 13, 6, (2006), 601-606. DOI: 10.3745/KIPSTB.2006.13.6.601.

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