Comparison of Vision Transformers and Convolutional Neural Networks in Medical Image Analysis: A Systematic Review

In the rapidly evolving field of medical image analysis utilizing artificial intelligence (AI), the selection of appropriate computational models is critical for accurate diagnosis and patient care. This literature review provides a comprehensive comparison of vision transformers (ViTs) and convolutional neural networks (CNNs), the two leading techniques in the field of deep learning in medical imaging. We conducted a survey systematically. Particular attention was given to the robustness, computational efficiency, scalability, and accuracy of these models in handling complex medical datasets. The review incorporates findings from 36 studies and indicates a collective trend that transformer-based models,…

• MO
  Ministry of Education, Culture, Sports, Science and Technology
• CO
  Cabinet Office, Government of Japan
• JS
  Japan Society for the Promotion of Science

  Award: 22K16700