DocumentCode :
3646842
Title :
Staging of the liver fibrosis from CT images using texture features
Author :
Ömer Kayaalti;Bekir H. Aksebzeci;Ibrahim Ö. Karahan;Kemal Deniz;Menmet Öztürk;Bülent Yilmaz;Sadik Kara;Musa H. Asyali
Author_Institution :
Develi Hü
fYear :
2012
fDate :
4/1/2012 12:00:00 AM
Firstpage :
47
Lastpage :
52
Abstract :
Even though liver biopsy is critical for evaluating chronic hepatitis and fibrosis, it is an invasive, costly, and difficult to standardize approach. The developments in medical image processing and artificial intelligence methods have advanced the potential of using computer-aided diagnosis techniques in the classification of liver tissues. The aim of this study was to develop a non-invasive, cost-effective, and fast approach to specify fibrosis stage using the texture properties of computed tomography images of liver. Gray level co-occurrence matrix, discrete wavelet transform, and discrete Fourier transform were the image analysis tools in the feature extraction phase. Following dimension reduction of the texture features support vector machines and k-nearest neighbor methods were used in the classification phase of this study. Our results showed that our approach is feasible in fibrosis staging especially in pairwise stage comparisons with success rate of approximately 90%.
Keywords :
"Liver","Support vector machines","Computed tomography","Educational institutions","Discrete wavelet transforms","Discrete Fourier transforms"
Publisher :
ieee
Conference_Titel :
Health Informatics and Bioinformatics (HIBIT), 2012 7th International Symposium on
Print_ISBN :
978-1-4673-0879-3
Type :
conf
DOI :
10.1109/HIBIT.2012.6209041
Filename :
6209041
Link To Document :
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