Characterization of Brain Tumors in Magnetic Resonance Images Using Texture Analysis

Abstract

This study was carried out in order to characterize of brain tumor in MRI by applying texture analysis to the brain tissues represented on MRI to recognizes the brain tumors from the other brain tissues which included: grey and white matter, fatty tissue, CSF and brain tumor. This study was carried out in the period from April 2020 to October 2020 in Khartoum state at Antalya diagnostic center. The images were obtained by (Signa HDxt 1.5 Tesla MRI systems). The data of this study collected from 50 patients having axial views that include brain tumor and they were selected randomly from a set of 50 MR images from 5 patients. the data were extracted from the image using 3×3 pixels window inside the window the first order and second order statistics were calculated and used to classify the brain MRI into one of the four tissues mentioned earlier. The window scans the whole image by interlacing it one pixel horizontally, then start again from the send line when the above one was completed till the end of the image. The results of this study showed that the overall accuracy of classification process was 94.8% and for the tumor the sensitivity was 80.8% white matter and grey matter showed a classification accuracy of 89.6% and for CSF was 82.5% and fatty tissue 71.9%. In conclusion these results showed that brain tumor can be classified successfully and delineated using texture analysis with a minimum effort