Efficient and Accurate Brain Tumor Classification Using Hybrid MobileNetV2–Support Vector Machine for Magnetic Resonance Imaging Diagnostics in Neoplasms

Efficient and Accurate Brain Tumor Classification Using Hybrid MobileNetV2–Support Vector Machine for Magnetic Resonance Imaging Diagnostics in Neoplasms

Background/Objectives: Magnetic Resonance Imaging (MRI) plays a vital role in brain tumor diagnosis by providing clear visualization of soft tissues without the use of ionizing radiation. Given the increasing incidence of brain tumors, there is an urgent need for reliable diagnostic tools, as misdia...

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Bibliographic Details
Main Authors: Mohammed Jajere Adamu, Halima Bello Kawuwa, Li Qiang, Charles Okanda Nyatega, Ayesha Younis, Muhammad Fahad, Salisu Samaila Dauya
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Brain Sciences
Subjects:
MR images
brain tumor
classification
machine and deep learning
MobileNetV2
SVM
Online Access:https://www.mdpi.com/2076-3425/14/12/1178
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