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CLASSIFICATION OF BRAIN TUMOR USING RECURRENT NEURAL NETWORKS

  • Unique Paper ID: 146597
  • Volume: 5
  • Issue: 1
  • PageNo: 139-144
  • Abstract:
  • Brain is an organ that controls activities of all the parts of the body. Recognition of automated brain tumor in Magnetic resonance imaging (MRI) is a difficult task due to complexity of size and location variability. This automatic method detects all the type of cancer present in the body. Previous methods for tumor are time consuming and less accurate. In the present work, statistical analysis morphological and thresholding techniques are used to process the images obtained by MRI. Feed-forward back-prop neural network is used to classify the performance of tumors part of the image. This method results high accuracy and less iterations detection which further reduces the consumption time.
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Cite This Article

  • ISSN: 2349-6002
  • Volume: 5
  • Issue: 1
  • PageNo: 139-144

CLASSIFICATION OF BRAIN TUMOR USING RECURRENT NEURAL NETWORKS

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Impact Factor
8.01 (Year 2024)
UGC Approved
Journal no 47859

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