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

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...

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Bibliographic Details
Published in:International Conference on Signal Processing and Integrated Networks (Online) pp. 208 - 211
Main Authors: Swami, Mahesh, Verma, Divya
Format: Conference Proceeding
Language:English
Published: IEEE 01.02.2020
Subjects:
Biomedical imaging
Brain tumour
Cancer
cancer detection
Computed tomography
image processing
Image segmentation
Magnetic resonance imaging
morphological operations
Radiographs
segmentation
Sensitivity
Tumors
ISSN:2688-769X
Online Access:Get full text
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Summary: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.
ISSN:2688-769X
DOI:10.1109/SPIN48934.2020.9070884