Brain tumor classification from MRI images using a multi-scale channel attention CNN integrated with SVM

Accurate classification of brain tumors from Magnetic Resonance Imaging (MRI) images remains a significant technical challenge in medical image analysis. Recent advancements have primarily focused on developing automated image classification methods. However, traditional convolutional neural networks (CNNs) have limited feature extraction capabilities, leading to suboptimal recognition performance. To address this issue, this paper proposes a novel image classification framework named multi-scale channel attention CNN integrated with support vector machine (MCACNN-SVM). In the proposed MCACNN-SVM, hierarchical spatial features are extracted with multi-scale convolutional kernels, and then further adaptively…

• MO
  Ministry of Education of the People's Republic of China