Wavelet analysis of the liver from CT datasets

Lambrou, T., Linney, A. and Todd-Pokropek, A. (2007) Wavelet analysis of the liver from CT datasets. International Journal of Computer Assisted Radiology and Surgery, 2 (1 SUPP). S96-S98. ISSN 1861-6410

Full content URL: http://dx.doi.org/10.1007/s11548-007-0086-4

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Item Type:Article
Item Status:Live Archive


In this paper a feasibility study of liver CT dataset classification, using features from different scales of the wavelet transform analysis in conjunction with statistical pattern recognition methods is presented. In our study 850 extracted sub-images from 19 liver CT scans were used. Statistical measurements were collected; from the sub-images as well as from their different scale wavelet transform coefficients. We found by using the Leave-One-Out method that the combination of the features from the first and second Order statistics, achieved overall classification accuracy >90.0, both specificity and sensitivity >90.0. Features selected by the spatial domain performed better than the wavelet based techniques, under the classification rule of Quadratic Classifier (QC). In addition, features selected by the third scale wavelet transform coefficients performed better than those collected from the other wavelet scales, under the classification rule of Bayesian Classifier (BC).

Keywords:Liver, Computed Tomography, Pattern recognition
Subjects:G Mathematical and Computer Sciences > G740 Computer Vision
Divisions:College of Science > School of Computer Science
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ID Code:8673
Deposited On:13 May 2013 11:34

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