Attention-Based Decision Fusion for Breast Cancer Classification Using Ensemble Transformers Topluluk D n st r c ler Kullanarak Dikkat Tabanli Karar Birle stirme ile Meme Kanseri Siniflandirmasi

Guzel K., BİLGİN G.

33rd IEEE Conference on Signal Processing and Communications Applications, SIU 2025, İstanbul, Türkiye, 25 - 28 Haziran 2025, (Tam Metin Bildiri) identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/siu66497.2025.11112389
  • Basıldığı Şehir: İstanbul
  • Basıldığı Ülke: Türkiye
  • Anahtar Kelimeler: attention mechanism, breast cancer, decision fusion, deep learning, ensemble learning, histopathological images, Vision transformers
  • Yıldız Teknik Üniversitesi Adresli: Evet

Özet

Breast cancer is a significant global health issue, and early diagnosis and accurate diagnostic processes are of great importance. In this study, deep learning-based transformer models were fine-tuned using a transfer learning approach for the classification of breast cancer histopathological images, and an attention mechanism-based decision fusion method was proposed to optimize model predictions. Experiments conducted on a widely used dataset in the literature demonstrated that the highest classification performance among individual models was achieved with an accuracy rate of 92.25%. However, using the proposed attention-based fusion method, an accuracy rate of 95% was attained on the test set. Additionally, analyses performed on an independent hidden test dataset to evaluate the model's generalization capability achieved an accuracy rate of 90%, indicating that the proposed method provides an effective solution for breast cancer classification.