Ms. Maryam Al Jaziri Profile

Maryam Al Jaziri

at Univ of Sharjah

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Proceedings Article | 18 June 2024 Poster + Paper

Brain tumor detection using machine learning

Talal Bonny, Maryam Al Jaziri, Mohammad Al-Shabi

Proceedings Volume 12998, 129981V (2024) https://doi.org/10.1117/12.3014635

KEYWORDS: Tumors, Brain, Cancer detection, Machine learning, Artificial intelligence

Read Abstract +

Brain tumors represent a critical health challenge, underscoring the urgency of accurate detection for timely intervention. Our study addresses this vital need by employing advanced machine learning techniques. We introduce a novel approach utilizing Convolutional Neural Networks (CNNs) for precise brain tumor classification. Our method involves custom data preparation, a network design and thorough training to improve precision. Additionally, we incorporate the known VGG16 structure into our strategy. Initial findings demonstrate the promise of our algorithm, the VGG16 version in outperforming techniques, for identifying brain tumors. With a remarkable 91.00% accuracy rate for VGG16 - Scenario 1 and a significantly improved 78.33% accuracy for CNN - Scenario 2, our findings highlight the superiority of our CNN-based methodology in achieving higher accuracy. As we continue to refine our approach, we anticipate making significant contributions to the medical field’s ability to accurately diagnose brain tumors.

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