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An algorithmic detection of brain tumour usingc image filtering and segmentation of various radiographs


Scalable and Secure Big Data I

3D Reconstruction in Canonical

A Hierarchical Image Matting M
Abstract


Cancer as a disease has taken the form of an epidemic for human beings. This work processes radiograph CT and MRI images to perform detection of brain tumour using a hybrid algorithm based on image processing and segmentation. The database taken is from Google open source brain scans and the system has been developed on MATLAB v2019 for Windows. Section I reviews image processing for medical imaging and Section II reviews associated state-of-art literature. Section III details the proposed system. An engineering analysis is detailed in Section IV; a sensitivity of 100%, similarity of 89.66% and accuracy of 87.50% is achieved for the algorithm. This work proposes to develop a cost-effective system accessible to medical practitioners on everyday computers.

KeyWords
Brain tumour, cancer detection, image processing, segmentation, Radiographs, morphological operations, sensitivity



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