Litcius/Paper detail

Classification & Feature extraction of Brain tumor from MRI Images using Modified ANN Approach

Harendra Singh, Roop Singh Solanki

2021International Journal of Electrical and Electronics Research14 citationsDOIOpen Access PDF

Abstract

In this research paper, a new modified approach is proposed for brain tumor classification as well as feature extraction from Magnetic Resonance Imaging (MRI) after pre-processing of the images. The discrete wavelet transformation (DWT) technique is used for feature extraction from MRI images and Artificial Neural Network (ANN) is used for the classification of the type of tumor according to extracted features. Mean, Standard deviation, Variance, Entropy, Skewness, Homogeneity, Contrast, Correlation are the main features used to classify the type of tumor. The proposed model can give a better result in comparison with other available techniques in less computational time as well as a high degree of accuracy. The training and testing accuracies of the proposed model are 100% and 98.20% with a 98.70 % degree of precision respectively.

Topics & Concepts

Artificial intelligencePattern recognition (psychology)Feature extractionEntropy (arrow of time)Computer scienceWaveletArtificial neural networkKurtosisStandard deviationTransformation (genetics)PreprocessorSkewnessBrain tumorMathematicsStatisticsGeneBiochemistryPathologyPhysicsChemistryMedicineQuantum mechanicsBrain Tumor Detection and ClassificationNeural Networks and ApplicationsDigital Imaging for Blood Diseases