Brain Tumour Detection using Deep Learning Technique

R. Meena*, S. Sharmila**, E. Sheela***, K. Thamizharasi****
*-**** Department of Biomedical Engineering, Gnanamani College of Technology, Namakkal, Tamilnadu, India.
Periodicity:January - June'2024
DOI : https://doi.org/10.26634/jpr.11.1.20824

Abstract

Recent advancements in medical imaging technology, such as integrating InceptionV3 algorithms with MRI scans, have revolutionized brain tumor detection. These algorithms leverage deep learning to analyze MRI images rapidly and accurately, aiding in the precise identification of potential tumors. This integration enhances the efficiency of radiologists, enabling timely interventions and improving patient outcomes. The seamless synergy between MRI technology and deep learning algorithms marks a significant leap forward in neurology, promising more personalized and effective care for patients with brain tumors. Ongoing innovation in medical imaging and AI holds great potential for further improving diagnostic accuracy and treatment effectiveness in the future.

Keywords

Neural Networks, Convolutional Neural Networks (CNNs), Medical Imaging, MRI Scan Analysis, Tumor Classification, Image Segmentation, Artificial Intelligence.

How to Cite this Article?

Meena, R., Sharmila, S., Sheela, E., and Thamizharasi, K. (2024). Brain Tumour Detection using Deep Learning Technique. i-manager’s Journal on Pattern Recognition, 11(1), 1-6. https://doi.org/10.26634/jpr.11.1.20824

References

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[10]. World Health Organization. (2019). Indonsia source GLOBOCAN 2018. The International Agency for Research on Cancer (IARC), 256, 1-2.
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