Feature statistic analysis of ultrasound images of liver cancer

Shuqin Huang; Mingyue Ding; Songgeng Zhang

doi:10.1117/12.748611

14 November 2007 Feature statistic analysis of ultrasound images of liver cancer

Shuqin Huang, Mingyue Ding, Songgeng Zhang

Proceedings Volume 6789, MIPPR 2007: Medical Imaging, Parallel Processing of Images, and Optimization Techniques; 67890N (2007) https://doi.org/10.1117/12.748611
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

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.

Citation Download Citation

Shuqin Huang, Mingyue Ding, and Songgeng Zhang "Feature statistic analysis of ultrasound images of liver cancer", Proc. SPIE 6789, MIPPR 2007: Medical Imaging, Parallel Processing of Images, and Optimization Techniques, 67890N (14 November 2007); https://doi.org/10.1117/12.748611

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