Development of Efficient Brain Tumour Detection and Classification Algorithm using Deep Learning Methods

Authors

  • A Vinisha ,Dr. Ravi Boda ,Dr Rahul Mukundrao Mulajkar

Keywords:

Brain tumor detection, Deep learning, Convolutional neural networks, Medical image analysis, ResNet architecture, Attention mechanisms, Squeeze-and-excitation, MRI classification, Computer-aided diagnosis, Medical artificial intelligence

Abstract

The increasing incidence of brain tumors worldwide, affecting approximately 350,000individuals annually, necessitates the development of advanced diagnostic methodologiesthat can provide accurate, rapid, and reliable detection capabilities. Traditional manual

References

Bouhafra, S., El Bahi, H. (2025). Deep Learning Approaches for Brain Tumor Detection and Classification Using MRI Images (2020 to 2024): A Systematic Review. Journal of Digital Imaging and Informatics in Medicine, 38, 1403-1433. Available at: https://link.springer.com/article/10.1007/s10278-024-01283-8

Chattopadhyay, A., Maitra, M. (2022). MRI-based brain tumor image detection using CNN based deep learning method. Neuroscience Informatics, 2, 100060. Available at: https://www.sciencedirect.com/science/article/pii/S277252862200022X

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Published

2024-05-20

How to Cite

A Vinisha ,Dr. Ravi Boda ,Dr Rahul Mukundrao Mulajkar. (2024). Development of Efficient Brain Tumour Detection and Classification Algorithm using Deep Learning Methods. Journal of Computational Analysis and Applications (JoCAAA), 33(05), 2279–2305. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/3321

Issue

Vol. 33 No. 05 (2024): JOCAAA

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.