Detection of Brain Tumor Using Neural Networks

  • Unique Paper ID: 168797
  • Volume: 11
  • Issue: 5
  • PageNo: 2083-2088
  • Abstract:
  • Brain tumors are life-threatening conditions requiring early detection and accurate diagnosis. Traditional magnetic resonance imaging (MRI) analysis methods are time-consuming and prone to human error. This study proposes a deep learning-based approach using neural networks for automated brain tumor detection. Our model utilizes convolutional neural networks (CNNs) to analyze MRI images and detect tumors with high accuracy. The proposed architecture consists of [insert architecture details, e.g., number of layers, activation functions]. We evaluated our model on a dataset of [insert dataset details, e.g., number of images, tumor types]. Results show that our approach achieves [insert performance metrics, e.g., accuracy, sensitivity, specificity] of [insert values, e.g., 95%, 92%, 96%] compared to traditional methods. Our findings demonstrate the potential of neural networks in improving brain tumor detection, enabling timely and effective treatment.

Cite This Article

  • ISSN: 2349-6002
  • Volume: 11
  • Issue: 5
  • PageNo: 2083-2088

Detection of Brain Tumor Using Neural Networks

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