Arterial Spin Labeling (ASL) Denoising with Markov Random Field (MRF) Optimization

Yongsheng Zhang¹, Ze Wang¹

ASL MRI has an intrinsic low signal-to-noise-ratio, requiring an efficient denoising method. Spatial smoothing is efficient for suppressing random noise but at the expense of a resolution loss. We proposed a resolution preserving ASL denoising method based on the Markov random field theory. Our evaluation results showed that the proposed method can gain up to 4 fold SNR increase while still keep the structural details intact. By contrast, spatial smoothing induced severe blurring effects when a similar level of SNR increase was achieved.