DOI: 10.36347/sjams.2016.v04i08.004

Pages: 2750-2754

The aim of this work to classification of regions in CT Abdomen where we define the hepatocellular carcinoma, liver, spine and ribs, the features of the classified regions of the whole images (as raw data) were classified furthers using linear discriminate analysis. The result of the classification showed that the HCC areas were classified well from the rest of the tissues although it has characteristics mostly similar to surrounding tissue. Several texture features are introduced using Daubechies wavelet, The Daubechies wavelet measures the gray level variations in a CT images, and it complements the coefficient of Daubechies wavelet Features extracted from the coefficient can be used to estimate the size distribution of the sub patterns. The Daubechies wavelet and its features seem very useful in texture classification. The classification accuracy of hepatocellular carcinoma 97.1 %, liver accuracy 91.7 %, While the spine and ribs showed a classification accuracy of 97.1, 91.2 % respectively.