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Publication Type : Journal
Publisher : International Journal of Advanced science and Technology
Source : International Journal of Advanced science and Technology, Vol. 29, No. 6, pp. 6500-6509.
Campus : Chennai
School : School of Engineering
Center : Amrita Innovation & Research
Department : Electronics and Communication
Verified : Yes
Year : 2020
Abstract : Brain tumor is the most destructive disease which leads to a very short life expectancy in the highest grade. Manual brain tumor diagnosis with a single image is less accurate yet still a time-consuming procedure. So, Multi-modal Fusion technique is adopted which merges two or more images to obtain a highly informative image with increased accuracy. In this paper, CNN based fusion algorithm is proposed to combine the computed tomography (CT) and magnetic resonance imaging (MRI) images in wavelet domain. The proposed method uses deep learning to fuse the images through the feature maps and obtain its features for further classification. Experimental results show that, the tumour can be detected accurately which will be useful for diagnosis. Further, the information is updated in the webserver using an IOT device which helps the clinicians for future investigations. Experimental results gives fused multimodal medical images of high quality with better statistical assessments as compared to existing methods
Cite this Research Publication : Aishwarya N, Praveena NG, Rajalakshmi B, Reshma R, Rizwana Begum B and Sowmya D, “Detection of Brain Tumor by Image Fusion based on Convolutional Neural Network”, International Journal of Advanced science and Technology, Vol. 29, No. 6, pp. 6500-6509.