Advantages of transformer and its application for medical image segmentation: a survey.

Journal: Biomedical engineering online
PMID: 38310297

Abstract

PURPOSE: Convolution operator-based neural networks have shown great success in medical image segmentation over the past decade. The U-shaped network with a codec structure is one of the most widely used models. Transformer, a technology used in natural language processing, can capture long-distance dependencies and has been applied in Vision Transformer to achieve state-of-the-art performance on image classification tasks. Recently, researchers have extended transformer to medical image segmentation tasks, resulting in good models.

Authors

  • Qiumei Pu
    School of Information Engineering, Minzu University of China, Beijing, China.
  • Zuoxin Xi
    School of Information Engineering, Minzu University of China, Beijing, 100081, China.
  • Shuai Yin
    School of Information Engineering, Minzu University of China, Beijing, 100081, China.
  • Zhe Zhao
    Paul G. Allen School for Global Animal Health, Washington State University, Pullman, WA, United States.
  • Lina Zhao
    College of Food and Bioengineering, Henan University of Science and Technology, Luoyang, China.

Keywords

External Resources

Popular Topics
Recent Journals