A Comprehensive Study on Brain Tumor and Stroke Detection from MRI Images Using Machine Learning Techniques

Authors

  • Rupak Kumar,Dr. Rashi Agarwal ,Dr. Renu Jain

Keywords:

Brain Tumor, Stroke, MRI, Machine Learning, Deep Learning, Image Segmentation, Feature Extraction, Classification.

Abstract

The human brain produces every action, thought, remembrance, sense, and understanding ofthe world. Structural changes in the brain cause brain abnormalities, such as tumors andstrokes, which are the most commonly occurring neurological disorders. Detecting and
analyzing these abnormalities

References

Abd-Ellah, MK, Awad, AI, Khalaf, AA & Hamed, HF 2016, 'Design and implementation of a computer-aided diagnosis system for brain tumor classification', Proceedings of 28th International Conference on Microelectronics, pp. 73-76.

Abd-Ellah, MK, Awad, AI, Khalaf, AA & Hamed, HF 2018, 'Two-phase multi-model automatic brain tumour diagnosis system from magnetic resonance images using convolutional neural networks', EURASIP Journal on Image and Video Processing, vol. 97, pp. 1-10.

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Published

2024-01-20

How to Cite

Rupak Kumar,Dr. Rashi Agarwal ,Dr. Renu Jain. (2024). A Comprehensive Study on Brain Tumor and Stroke Detection from MRI Images Using Machine Learning Techniques . Journal of Computational Analysis and Applications (JoCAAA), 32(1), 1108–1120. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/3803

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Section

Articles