Advanced Approaches to Brain Tumor Classification and Diagnosis

International Journal of Electronics and Communication Engineering

© 2022 by SSRG - IJECE Journal

Volume 9 Issue 1

Year of Publication : 2022

Authors : G Jeyalakshmi, K.A Shahul Hameed

10.14445/23488549/IJECE-V9I1P102

How to Cite?

G Jeyalakshmi, K.A Shahul Hameed, "Advanced Approaches to Brain Tumor Classification and Diagnosis," SSRG International Journal of Electronics and Communication Engineering, vol. 9,  no. 1, pp. 6-9, 2022. Crossref, https://doi.org/10.14445/23488549/IJECE-V9I1P102

Abstract:

In hospitals, the data about the presence andposition of brain tumours (BT) is important to support clinicians in analysis and treatment. Automatic BT segmentation on the images attained by magnetic resonance imaging (MRI) is the best method to achieve this data. Recently, machine learning (ML) and deep learning (DL) algorithms have been introduced to accurately process MRI images to classify brain tumour stages. This article reviews various ML and DL algorithms proposed in brain tumour segmentation and classification algorithms.

Keywords:

A brain tumour, Deep learning and Machine learning.

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