8 February 2017 A liver cirrhosis classification on B-mode ultrasound images by the use of higher order local autocorrelation features
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Proceedings Volume 10225, Eighth International Conference on Graphic and Image Processing (ICGIP 2016); 102250U (2017) https://doi.org/10.1117/12.2266914
Event: Eighth International Conference on Graphic and Image Processing, 2016, Tokyo, Japan
Abstract
In this paper, in order to classify liver cirrhosis on regions of interest (ROIs) images from B-mode ultrasound images, we have proposed to use the higher order local autocorrelation (HLAC) features. In a previous study, we tried to classify liver cirrhosis by using a Gabor filter based approach. However, the classification performance of the Gabor feature was poor from our preliminary experimental results. In order accurately to classify liver cirrhosis, we examined to use the HLAC features for liver cirrhosis classification. The experimental results show the effectiveness of HLAC features compared with the Gabor feature. Furthermore, by using a binary image made by an adaptive thresholding method, the classification performance of HLAC features has improved.
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Kenya Sasaki, Yoshihiro Mitani, Yusuke Fujita, Yoshihiko Hamamoto, Isao Sakaida, "A liver cirrhosis classification on B-mode ultrasound images by the use of higher order local autocorrelation features", Proc. SPIE 10225, Eighth International Conference on Graphic and Image Processing (ICGIP 2016), 102250U (8 February 2017); doi: 10.1117/12.2266914; https://doi.org/10.1117/12.2266914
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