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KMID : 1151820150090060369
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Journal of the Korean Society of Radiology
2015 Volume.9 No. 6 p.369 ~ p.374
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Texture Feature Analysis Using a Brain Hemorrhage Patient CT Images
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Park Hyong-Hu
Park Ji-Koon
Choi Il-Hong
Kang Sang-Sik
Noh Si-Cheol
Joeng Bong-Jae
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Abstract
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In this study we proposed a texture feature analysis algorithm that distinguishes between a normal image and a diseased image using CT images of some brain hemorrhage patients, and generates both Eigen images and test images which can be applied to the proposed computer aided diagnosis system in order to perform a quantitative analysis for 6 parameters. And through the analysis, we derived and evaluated the recognition rate of CT images of brain hemorrhage. As the results of examining over 40 example CT images of brain hemorrhage, the recognition rates representing a specific texture feature-value are as follows: some appeared to be as high as 100% including average gray level, average contrast, smoothness, and Skewness while others showed a little low disease recognition rate: 95% for uniformity and 87.5% for entropy. Consequently, based on this research result, if a software that enables a computer aided diagnosis system for medical images is developed, it will lead to the availability for the automatic detection of a diseased spot in CT images of brain hemorrhage and quantitative analysis. And they can be used as computer aided diagnosis data, resulting in the increased accuracy and the shortened time in the stage of final reading.
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KEYWORD
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Texture Feature Analysis, Brain Hemorrhage, Recognition Rate
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