BrainNet: Optimal Deep Learning Feature Fusion for Brain Tumor Classification

Early detection of brain tumors can save precious human life. This work presents a fully automated design to classify brain tumors. The proposed scheme employs optimal deep learning features for the classification of FLAIR, T1, T2, and T1CE tumors. Initially, we normalized the dataset to pass them t...

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Detalles Bibliográficos
Autores principales: Zahid, Usman, Ashraf, Imran, Khan, Muhammad Attique, Alhaisoni, Majed, Yahya, Khawaja M., Hussein, Hany S., Alshazly, Hammam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9371837/
https://www.ncbi.nlm.nih.gov/pubmed/35965745
http://dx.doi.org/10.1155/2022/1465173

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9371837/
https://www.ncbi.nlm.nih.gov/pubmed/35965745
http://dx.doi.org/10.1155/2022/1465173

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