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A Survey on Brain Tumor Detection from MRI Images Using Machine Learning Techniques

Royyuru Srikanth, N. Kanya and P.S. Raja Kumar


The accelerated and unchecked cell growth that leads to brain tumors. It can cause death if not treated right away. Accurate segmentation and classification are still challenging tasks, despite significant efforts and encouraging outcomes in this area. The variation in tumor location, shape, and size presents a significant challenge to the detection of brain tumors. In order to help researchers, this survey aimed to compile all available literature on brain tumor detection by magnetic resonance imaging (MRI) images. This research covers a wide range of issues relevant to the study of brain tumors, from tumor anatomy to publicly available datasets to state-of-the-art methodologies to segmentation to feature extraction to classification to machine learning (ML) to transformational learning to quantum ML. Finally, this article grants a thorough analysis of all major publications on brain tumour identification from MRI scans using ML algorithms, including their contributions, limitations, recent advances, and proposed directions for future research.

Published on: December 05, 2023
doi: 10.17756/nwj.2023-s4-076
Citation: Srikanth R, Kanya N, Kumar PSR. 2023. A Survey on Brain Tumor Detection from MRI Images Using Machine Learning Techniques. NanoWorld J 9(S4): S452-S461.

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