The article presents the Vision Mamba DDPM model, which innovatively combines CNNs and State Space Models (SSM) to enhance the synthesis of medical images. This new approach addresses the balance between local perceptual capabilities and global informative content, which is crucial in medical diagnostic processes.

• Authors: Zhihan Ju, Wanting Zhou
• Published: May 2024
• Highlights:
  • Develops MSSBlock and SSLayer to optimize feature extraction and encoding in medical imaging.
  • Introduces a zero-parameter Sequence Regeneration strategy, enhancing spatial feature perception.
  • Achieves state-of-the-art performance in synthesizing accurate and clinically applicable medical images.

Significance: VM-DDPM represents a significant leap in medical image synthesis, offering a robust model that enhances both the depth and the utility of synthesized images for clinical use. The integration of SSM and CNN architectures opens new avenues for research in image processing, particularly in the highly sensitive area of medical diagnostics.