Cross prior Bayesian attention with correlated inception and residual learning for brain tumor classification using MR images (CB-CIRL Net).

Journal: Journal of neuroscience methods
Published Date:

Abstract

BACKGROUND: Brain tumor classification from magnetic resonance (MR) images is crucial for early diagnosis and effective treatment planning. However, the homogeneity of tumors across different categories poses a challenge. Although, attention-based convolutional neural networks (CNNs) approaches have shown promising results in brain tumor classification, simultaneous consideration of both spatial and channel-specific features remains limited.

Authors

  • B Vijayalakshmi
    Department of Electronics and Communication Engineering, Mepco Schlenk Engineering College, Sivakasi, Tamil Nadu 626 005, India. Electronic address: vijayalakshmib@mepcoeng.ac.in.
  • S Anand
    Department of Electronics and Communication Engineering, Mepco Schlenk Engineering College, Sivakasi, Tamil Nadu 626 005, India. Electronic address: sanand@mepcoeng.ac.in.