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Noise Level Adaptive Diffusion Model for Robust Reconstruction of Accelerated MRI
March 11, 2024, 4:45 a.m. | Shoujin Huang, Guanxiong Luo, Xi Wang, Ziran Chen, Yuwan Wang, Huaishui Yang, Pheng-Ann Heng, Lingyan Zhang, Mengye Lyu
cs.CV updates on arXiv.org arxiv.org
Abstract: In general, diffusion model-based MRI reconstruction methods incrementally remove artificially added noise while imposing data consistency to reconstruct the underlying images. However, real-world MRI acquisitions already contain inherent noise due to thermal fluctuations. This phenomenon is particularly notable when using ultra-fast, high-resolution imaging sequences for advanced research, or using low-field systems favored by low- and middle-income countries. These common scenarios can lead to sub-optimal performance or complete failure of existing diffusion model-based reconstruction techniques. Specifically, …
abstract acquisitions arxiv cs.ai cs.cv data diffusion diffusion model eess.iv general however images imaging mri noise robust type world
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