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Proceedings Paper

Feature statistic analysis of ultrasound images of liver cancer
Author(s): Shuqin Huang; Mingyue Ding; Songgeng Zhang
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Paper Abstract

In this paper, a specific feature analysis of liver ultrasound images including normal liver, liver cancer especially hepatocellular carcinoma (HCC) and other hepatopathy is discussed. According to the classification of hepatocellular carcinoma (HCC), primary carcinoma is divided into four types. 15 features from single gray-level statistic, gray-level co-occurrence matrix (GLCM), and gray-level run-length matrix (GLRLM) are extracted. Experiments for the discrimination of each type of HCC, normal liver, fatty liver, angioma and hepatic abscess have been conducted. Corresponding features to potentially discriminate them are found.

Paper Details

Date Published: 14 November 2007
PDF: 7 pages
Proc. SPIE 6789, MIPPR 2007: Medical Imaging, Parallel Processing of Images, and Optimization Techniques, 67890N (14 November 2007); doi: 10.1117/12.748611
Show Author Affiliations
Shuqin Huang, Huazhong Univ. of Science and Technology (China)
Mingyue Ding, Huazhong Univ. of Science and Technology (China)
Songgeng Zhang, Beijing Tsinghua R&D Industry Institute (China)


Published in SPIE Proceedings Vol. 6789:
MIPPR 2007: Medical Imaging, Parallel Processing of Images, and Optimization Techniques

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