Key Techniques Research in Computer-Aided Hepatic Lesion Diagnosis System Based on Multi-Phase CT Images
Computer-aided diagnosis (CAD) of liver diseases as an early non-invasive diagnosis is of great significance. This paper presents an automated diagnostic system for liver disease based on multiphase CT images. The region of the liver is first extracted from a CT image using improved watershed algorithm. After the registration of liver regions, which uses the SIFT algorithm, the operation of extracting the ROI based on Gabor wavelet transformation would be followed. Besides using image texture metric as the feature vector, we also designed a temporal and sacttergram-based lesion enhancement pattern descriptor to quantify the different lesions. Then, in the designing of classifier module, we convert a 4 classes classifying problem into 3 binary classify problems by using artificial neural network. Finally, we obtained the best classification accuracy of 0.9797, 0.9851 and 0.9753 for normal-abnormal, cyst-otherdisease and carcinoma-haemangioma sub problems respectively.
Computer-Aided Diagnosis Liver Lesion Watershed Wavelet Transform sattergram.
Shaohua Su Yan Sun
School of Software Shanghai Jiao Tong University Shanghai, China School of Software Shanghai Jiao Tong University Shanghai, China
国际会议
2011 4th International Congress on Image and Signal Processing(第四届图像与信号处理国际学术会议 CISP 2011)
上海
英文
1956-1962
2011-10-15（万方平台首次上网日期，不代表论文的发表时间）