Brain Tumor identification by Convolution Neural Network with Fuzzy C-mean Model Using MR 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.contributor.authorJavaid, Imran
dc.contributor.authorAhmad, Isah Salim
dc.date.accessioned2022-01-10T11:18:14Z
dc.date.available2022-01-10T11:18:14Z
dc.date.issued2020-12-29
dc.description.abstractMedical image computing techniques are essential in helping the doctors to support their decision in the diagnosis of the patients. Due to the complexity of the brain structure, we choose to use MR brain images because of their quality and the highest resolution. The objective of this article is to detect brain tumor using convolution neural network with fuzzy c-means model, the advantage of the proposed model is the ability to achieve excellent performance using accuracy, sensitivity, specificity, overall dice and recall values better than the previous models that are already published. In addition, the novel model can identify the brain tumor, using different types of MR images. The proposed model obtained accuracy with 98%.en_US
dc.identifier.issn1998-4464
dc.identifier.urihttps://uilspace.unilorin.edu.ng/handle/20.500.12484/7301
dc.language.isoenen_US
dc.publisherNorth Atlantic University Unionen_US
dc.subjectMRIen_US
dc.subjectCNNen_US
dc.subjectFCMen_US
dc.subjectTumor Detectionen_US
dc.subjectaccuracyen_US
dc.subjectsensitivityen_US
dc.subjectdiceen_US
dc.titleBrain Tumor identification by Convolution Neural Network with Fuzzy C-mean Model Using MR Brain Imagesen_US
dc.typeArticleen_US

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