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Research Article

Brain Tumour Detection Using Deep Learning and Angular

Open Access Peer Reviewed

Authors

  • Somaanath M U1
  • Hariharapranav R S2
  • Kowsik J3
  • Lavanya C4

1234 Computer Science & Engineering, Bannari Amman Institute of Technology, Tamil Nadu, India.

Article Information

DOI
No DOI
Published Online
March-April 2023
Pages
19-22
Article Type
Research Article
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No DOI available for cross-reference

Abstract

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Abstract: Brain tumor detection is an important area of research in the medical field. The early detection of brain tumors can significantly improve patient outcomes. In recent years, deep learning techniques have shown promising results in medical image analysis, including brain tumor detection. In this paper, we propose a combined CNN-RNN approach for brain tumor detection. Our proposed approach utilizes Convolutional Neural Networks (CNN) for feature extraction and Recurrent Neural Network (RNN) for temporal modelling of the features. Our proposed approach achieves state-of-the-art results on a publicly available brain tumor dataset, demonstrating the effectiveness of our proposed approach. With a considerable prediction performance of 99.1%, a precision of 98.8%, a recall of 98.9%, and an F1-measure of 99.0%, the suggested model accurately predicts the brain tumour.

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