Study on Brain Tumor Classification Through MRI Images Using a Deep Convolutional Neural Network

Study on Brain Tumor Classification Through MRI Images Using a Deep Convolutional Neural Network

Kirti Sharma, Ketna Khanna, Sapna Gambhir, Mohit Gambhir
Copyright: © 2022 |Pages: 19
DOI: 10.4018/IJIRR.289610
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Abstract

Brain tumor (Glioma) is one of the deadliest diseases that attack humans, now even men or women aged 20-30 are suffering from this disease. To cure tumor in a person, doctors use MRI machine, because the results of MRI images are proven to provide better image results than CT-Scan images, but sometimes it is difficult to distinguish between the MRI images having tumors with that images not having tumor from MRI image results. It is because of resulting contrast is like any other normal organ. However, using features of image processing techniques like scaling, contrast enhancement and thresh-holding based in Deep Neural Networks the scheme can classify the results more appropriately and with high accuracy. In this paper, this study reveals the nitty-gritty of Brain tumor (Gliomas) and Deep Learning techniques for better inception in the field of computer-vision.
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2. Background

Gliomas is a type of brain tumor. A Glial cell is the type of supportive cell which is present in our brain. Astrocytes, oligodendrocytes, and ependymal are the types of supportive cells. Grade is assigned to Glioma that basically indicates that how aggressive tumor is likely to be. If grade is high that means tumor is more aggressive and can grow quickly. Various types of glioma are gives below.

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