Brain Tumor Identification by Hybrid CNN-SWT Model
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Date
2022-05-24
Authors
Abd El Kader, Isselmou
Xu, Guizhi
Zhang, Shuai
Saminu, Sani
Javaid, Imran
Ahmad, Isah Salim
Kamhi, Souha
Journal Title
Journal ISSN
Volume Title
Publisher
Bentham Science Publishers Ltd
Abstract
Objective: Detecting brain tumor using the segmentationtechnique is a big challenge for researchers and takes a long time inmedical image processing. Magnetic resonance image analysis techniquesfacilitate the accurate detection of tissues and abnormal tumors in thebrain. The size of a brain tumor can vary with the individual and thespecifics of the tumor. Radiologists face great difficulty in diagnosing andclassifying brain tumors.
Method: This paper proposed a hybrid model-based convolutional neuralnetwork with a stationary wavelet trans-form named “CNN-SWT” tosegment brain tumors using MR brain big data. We utilized 7 layers forclassification in the proposed model that include 3 convolutional and 3ReLU. Firstly, the input MR image is divided into multiple patches, and thenthe central pixel value of each patch is provided to the CNN-SWT. Secondly,the pre-processing stage is per-formed using the mean filter to remove thenoise. Then the convolution neural network-layer approach is utilized tosegment brain tumors. After segmentation, robust feature extraction suchas information-extraction methods is used for the feature extractionprocess. Finally, a CNN-based hybrid scheme based on the stationarywavelet transform technique is used to detect tumors using MR brainimages.
Materials: These experiments were obtained using 11500 MR brain imagesdata from the hospital national of oncology.
Results: It was proved that the proposed hybrid achieved a highclassification accuracy of (98.7 %) as compared with existing methods.
Conclusion: The advantage of the hybrid novelty of the model and theability to detect the tumor area achieved excellent overall performanceusing different values.
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Keywords
Brain detection , classification , MR Images , convolution neuralnetwork , stationary wavelet transform , tumor