Modified Self-Organizing Map Algorithm for Brain Tumor Detection and Analysis Using Magnetic Resonance Brain Images

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dc.contributor.authorIsselmou, Abd El Kader
dc.contributor.authorGuizhi, Xu
dc.contributor.authorZhang, Shuai
dc.contributor.authorSaminu, Sani
dc.date.accessioned2022-01-10T11:12:20Z
dc.date.available2022-01-10T11:12:20Z
dc.date.issued2019-06-30
dc.description.abstractmedical image processing play an important role to help radiologists and support their decisions in diagnosis of the patient, magnetic resonance imaging (MRI) has ability to diagnosis the small details in the human body with a high resolution; in this paper, we propose modified self-organizing map algorithm (MSOM) for brain tumor detection and analysis using magnetic resonance brain images the significance of the (MSOM) algorithm is ability to detect tumor area in the magnetic resonance brain image (MRI) clearly with a high accuracy and best performance according of different values, the advantage of method proposed can segment and detect different types of MRI brain images FLAIR, T1 and T2-weight images with same performance and accuracy, the (MSOM) method start through input magnetic resonance brain image (MRI) and preprocessing applied to remove the noise from the image, applied modified selforganizing map (MSOM), applied tumor area, performance of the method, finally the applied of modified self-organizing map (MSOM) gave a best results us shown in the results.en_US
dc.identifier.issn2055-1266
dc.identifier.urihttps://uilspace.unilorin.edu.ng/handle/20.500.12484/7299
dc.language.isoenen_US
dc.publisherServices for Science and Education, United Kingdomen_US
dc.subjectMRIen_US
dc.subjectbrain tumor detectionen_US
dc.subjectmodified self-organizing mapen_US
dc.subjectaccuracy valuesen_US
dc.titleModified Self-Organizing Map Algorithm for Brain Tumor Detection and Analysis Using Magnetic Resonance Brain Imagesen_US
dc.typeArticleen_US

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