Authors :
Mohak Jani; Keith Dsouza; Nelson Dsouza; Dr. Joanne Gomes
Volume/Issue :
Volume 7 - 2022, Issue 2 - February
Google Scholar :
http://bitly.ws/gu88
Scribd :
https://bit.ly/3vvJtKv
DOI :
https://doi.org/10.5281/zenodo.6324441
Abstract :
Brain tumours are regarded as one of the most
dangerous diseases in both children and adults. Brain
tumours make up 85 to 90% of all primary Central
Nervous System tumours. Brain tumours are classified as
benign, malignant, pituitary, or other. Magnetic
Resonance Imaging is the most effective technique for
detecting brain tumours. The use of automated
classification techniques such as Machine Learning and
Artificial Intelligence has consistently demonstrated
greater accuracy than manual classification. The user can
use the proposed system as a Web Application. The
patient, doctor or medical practitioners, paramedic
etcetera are the users for the system. The proposed system
acts like an assistant to the doctor, by detecting brain
cancer in MRI images. The user will upload the brain MR
Image of the patient concerned. Then the system will be
able to predict whether the patient has cancer or not, if the
patient has cancer the category will be specified.
Experimental results indicate that the proposed approach
outperforms other commonly used methods and gives an
overall high validation accuracy
Keywords :
Machine Learning, Artificial Intelligence, Convolutional Neural Network, Transfer Learning, Brain Tumor.
Brain tumours are regarded as one of the most
dangerous diseases in both children and adults. Brain
tumours make up 85 to 90% of all primary Central
Nervous System tumours. Brain tumours are classified as
benign, malignant, pituitary, or other. Magnetic
Resonance Imaging is the most effective technique for
detecting brain tumours. The use of automated
classification techniques such as Machine Learning and
Artificial Intelligence has consistently demonstrated
greater accuracy than manual classification. The user can
use the proposed system as a Web Application. The
patient, doctor or medical practitioners, paramedic
etcetera are the users for the system. The proposed system
acts like an assistant to the doctor, by detecting brain
cancer in MRI images. The user will upload the brain MR
Image of the patient concerned. Then the system will be
able to predict whether the patient has cancer or not, if the
patient has cancer the category will be specified.
Experimental results indicate that the proposed approach
outperforms other commonly used methods and gives an
overall high validation accuracy
Keywords :
Machine Learning, Artificial Intelligence, Convolutional Neural Network, Transfer Learning, Brain Tumor.
