Abstract:
Early detection and classification of brain tumors, is one of the challenging tasks
for medical practitioners and plays a vital role in choosing the appropriate
treatment method that ensures an improved life expectancy for patients. Clinical
diagnosis is performed with biopsy which is not possible without brain surgery
and conventionally by inspecting the magnetic resonance images (MRI) which is
prone to human errors. A deep learning-based Convolutional Neural Network
(CNN) is used for three types of brain tumor classification in MRI with remarkable
performance and higher accuracy without any invasive methods. The proposed
CNN network architecture can be an excellent decision-support tool for Computer
Aided Diagnosis (CAD) of tumor cells with an accuracy of 97.6%.
