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Classification of Benign/Malignant PNGGOs using K-means algorithm in MDCT Images: A Preliminary Study

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Authors
Son, Wooram; Park, Sang Joon; Park, Chang Min; Goo, Jin Mo; Kim, Jong Hyo
Issue Date
2009-01-19
Publisher
Institute of Electronics, Information and Communication Engineers (IEICE)
Citation
IEICE Tech. Rep., vol.108, no.385, MI2008-115, pp.257-260, Jan. 2009.
Keywords
Computer-aided diagnosisClassificationlung cancerct
Abstract
Lung cancer is one of the most prevalent diseases in the world. Recently, PNGGOs (Pure nodular ground-glass opacity) have been reported to increasing aspect for all CT-detected pulmonary nodules. Moreover, the malignancy rate of PNGGOs is a considerable proportion of benign diseases. In this study, we have developed a computerized classification scheme of PNGGOs malignancy. Segmentation of PNGGOs was performed semi-automatically. After that, the histogram based statistical features and region based features of benign and malignant GGO was extracted. Finally, K-means classifier was applied. Experiment was performed employing 12 CT image sets and 91.67% of accuracy was achieved.
ISSN
0913-5685
Language
English
URI
http://hdl.handle.net/10371/5314
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