Diffusion-Assisted Frequency Attention Model for Whole-body Low-field MRI Reconstruction
This work addresses MRI reconstruction in resource-constrained clinical settings, representing an incremental improvement by combining existing techniques.
The paper tackled the problem of whole-body low-field MRI reconstruction under low-SNR conditions by integrating diffusion models with frequency-domain attention, resulting in a method that consistently outperforms conventional and recent learning-based approaches.
By integrating the generative strengths of diffusion models with the representation capabilities of frequency-domain attention, DFAM effectively enhances reconstruction performance under low-SNR condi-tions. Experimental results demonstrate that DFAM consistently outperforms both conventional reconstruction algorithms and recent learning-based approaches. These findings highlight the potential of DFAM as a promising solution to advance low-field MRI reconstruction, particularly in resource-constrained or underdeveloped clinical settings.