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Research Paper | Radiological Sciences | Sudan | Volume 7 Issue 7, July 2018 | Popularity: 6.9 / 10
Classification of Brain Tumor Using Texture Analysis
Auis Mohammed, Mohammed Garelnabi, Shazaly Khojaly, Shaza Elfadil
Abstract: Diagnosis of brain tumor is very critical ordinarily, this study presents a highly efficient method to identify, diagnosis and classify the intracranial tumors. Forty-nine CT images contain different types of intracranial tumor were selected, the procedure contain dual phase, phase one contain feature extraction from the selected images, phase two classification of images component according to the extracted features using linear discriminant analysis, the quantitative results showed that the proposed method has high accuracy in recognizing the intracranial tumor from the normal surrounding tissues. The accuracy of classification was 90.4 %.
Keywords: classification, texture feature, linear discriminant analysis, computed tomography CT, brain tumor
Edition: Volume 7 Issue 7, July 2018
Pages: 883 - 886
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