Keywords: Prostate, Diffusion Denoising, AI/ML Image Reconstruction, Prostate
Motivation: Multiparametric-MRI (mpMRI) of the prostate is integral in the detection, staging, treatment planning, and targeting for prostate cancer. Particularly diffusion weight imaging (DWI) provides a strong correlation with cancer grade. However, DWI, particularly at high b-value suffers from low SNR.
Goal(s): To improve image quality of DWI, particularly at high-b-value, for prostate MRI-guided clinical care.
Approach: This study employs a novel body-conforming high-density 50-Channel pelvic coil with additional perineal coverage and Deep Learning (DL) based reconstruction for denoising diffusion images.
Results: High density pelvic coil and DL-based reconstruction improves the image quality demonstrated in reader score and statistical measurements.
Impact: This study shows a clinically feasible approach by combining a novel 50-channel pelvic coil with perineal coverage with DL based reconstruction for an improved DWI imaging in prostate MR.
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