TEJAS Journal of Technologies and Humanitarian Science

A Comprehensive Review of Machine Learning Techniques for Brain Tumour Classification and Detection

Shalini Verma
M. Tech Scholar, Dept. of CSE, Goel Institute of Technology & Management, (AKTU), Lucknow, India

Author

Dr. Anita Pal
Associate Professors, Dept. of CSE, Goel Institute of Technology & Management, (AKTU), Lucknow, India

Author

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Abstract:

Because brain tumours vary widely in size, location, and form, diagnosing them can be extremely difficult. Although manual evaluation and conventional imaging techniques are still widely used, deep learning has become a game-changing technology for automated diagnosis. The study discussed in the thesis is summarised in this review, which also places it in the larger context of brain tumour detection methods. It addresses classical machine learning algorithms, the advent of convolutional neural networks (CNNs), and hybrid procedures. The report offers a thorough reference for audiences in academia and medicine by highlighting present strengths, enduring constraints, and prospects for further research.

References

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