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Student Publications [Scholarly]
Enhanced Breast Cancer Classification Using Attention-Augmented CNN and Multi-View Learning on the Inbreast Dataset
Document Type
Conference Proceeding
Abstract
Breast cancer remains a leading cause of mortality among women worldwide, emphasizing the critical need for accurate and early diagnosis. Convolutional Neural Networks (CNNs) have demonstrated remarkable performance in medical image analysis, particularly in mammographic classification tasks. Building upon prior work that employed a fine-tuned VGG-16 model combined with a Support Vector Machine (SVM) classifier on the INbreast dataset, this study proposes a novel extension to enhance both accuracy and interpretability. The proposed framework integrates Convolutional Block Attention Modules (CBAM) into the CNN architecture to enable adaptive feature refinement by focusing on salient spatial and channelwise information. Additionally, a dual-stream multi-view learning approach is introduced to leverage bilateral mammographic images, capturing cross-view contextual dependencies often overlooked in single-view analysis. To further improve classification performance, a lightweight Vision Transformer (ViT-lite) replaces the traditional SVM, facilitating effective global feature modeling through self-attention. Experimental results on the INbreast dataset demonstrate a significant improvement in classification accuracy, achieving 98.4%, along with enhanced precision, recall, and AUC scores. The proposed model not only advances the state-of-the-art in breast cancer classification but also provides a more interpretable and scalable solution, thereby contributing to the development of reliable computer-aided diagnostic tools in clinical settings. © 2025 IEEE.
Publication Title
2025 International Conference on Computing Technologies and Data Communication, ICCTDC 2025
Publication Date
2025
ISBN
9798331527983
DOI
10.1109/ICCTDC64446.2025.11159034
Keywords
attention mechanisms, breast cancer classification, Convolutional Neural Networks (CNN), INbreast dataset, multi-view learning, Vision Transformer (ViT)
Repository Citation
Akuthota, Sreeja, "Enhanced Breast Cancer Classification Using Attention-Augmented CNN and Multi-View Learning on the Inbreast Dataset" (2025). Student Publications [Scholarly]. 65.
https://commons.clarku.edu/student_publications/65
