Title of article
A Neural Network based Method for Brain Abnormality Detection in MR Images Using Gabor Wavelets
Author/Authors
AmirEhsan Lashkari، نويسنده ,
Issue Information
روزنامه با شماره پیاپی سال 2010
Pages
10
From page
6
To page
15
Abstract
Nowadays, automatic defects detection in MR images is very important in many diagnostic and therapeutic applications. This paper introduces a Novel automatic brain tumor detection method that uses T1, T2_weighted and PD, MR images to determine any abnormality in brain tissues. Here, has been tried to give clear description from brain tissues using Gabor wavelets, energy, entropy, contrast and some other statistic features such as mean, median, variance, correlation, values of maximum and minimum intensity .It is used from a feature selection method to reduce the feature space too. this method uses from neural network to do this classification. The purpose of this project is to classify the brain tissues to normal and abnormal classes automatically, that saves the radiologist time, increases accuracy and yield of diagnosis.
Keywords
Kernel F-score feature selection , feature extraction , artificial neural network , Tumor detection , segmentation , MR images , Gabor wavelets
Journal title
International Journal of Computer Applications
Serial Year
2010
Journal title
International Journal of Computer Applications
Record number
659895
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