Advanced Deep Learning Denoising for Accelerated 0.55T Prostate MRI

Motivation: Low-Field MR offers a great platform for low-cost high-performance screening of prostate cancer, but it suffers from low SNR. Prolonged scan times are typically needed to achieve adequate SNR at low field. Goal(s): In this work, we developed an advanced deep learning denoising method for rapid high spatial resolution prostate MRI at 0.55T. Approach: The proposed approach was tested in T2-weighted prostate MRI. Supervised training was performed to denoise images acquired with different numbers of averages, corresponding to different scan times. Results: Deep learning was able to denoise prostate images at high spatial resolution resulting acquisition time with 1-2 average. Impact: The proposed denoising technique holds significant potential to promote the use of 0.55T MRI and other types of low-field MRI for prostate imaging and screening for prostate cancer, with reduced cost and greater accessibility.