Brain Tumor Detection Using Deep Learning

Elroy Noronha; Pranit Pathak; Chaitra K.N

doi:10.21276/ijirem.2021.8.4.4

Abstract

A brain tumor is a disease caused due to the growth of abnormal cells in the brain. A brain tumor is categorized into two categories, cancerous brain tumor (malignant) and non-cancerous brain tumor (benign). Due to the rareness and various different types of tumors, the rate of survival of a tumor-prone patient is hard to predict. According to cancer research by the UK, fifteen out of a hundred people with brain cancer have a chance of survival of ten years or more after diagnosis. Treating a patient with a brain tumor is dependent on numerous factors such as: the type of tumor, abnormality of the cells and location of the tumor in the brain, etc. With the development in the field of Artificial Intelligence, diagnosis of brain tumors is done by using deep learning models using magnetic resonance imaging (MRI) scans. Magnetic Resonances Imaging (MRI) is a type of scanning method that uses strong magnetic fields and radio waves to produce detailed images of the inner body. The project uses VGG-16 architecture which is a deep learning model for detection of the tumors in scanned brain images.

Keywords

AI, Deep Learning, Machine Learning, CNN

References

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Cites this article as

E. N. , P. P. , C. K. , "Brain Tumor Detection Using Deep Learning", International Journal of Innovative Research in Engineering & Management (IJIREM), Vol-8, Issue-4, Page No-15-21, 2021. Available from: https://doi.org/10.21276/ijirem.2021.8.4.4

Corresponding Author

Elroy Noronha

Elroy Noronha, Student, Department of Electronics and Communication, Nitte Meenakshi Institute of Technology, Bengaluru, India (lroynoronha1998@gmail.com)