Meeting Banner
Abstract #4772

Reducing scan time of routine prostate diffusion-weighted imaging using random matrix theory reconstruction

Gregory Lemberskiy1,2, Yousef Mazaheri3, Herbert Alberto Vargas4, Ricardo Otazo3, Els Fieremans1, and Dmitry S Novikov1
1Radiology, New York University School of Medicine, New York, NY, United States, 2Microstructure Imaging INC, New York, NY, United States, 3Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United States, 4Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States

We propose Random Matrix Theory (RMT) reconstruction to reduce the scan time of prostate diffusion (DWI) by using fewer averages and still maintain image quality. RMT leverages the joint redundancy across receiver coils, voxels, and measurements to identify and remove the universal noise-only Marchenko-Pastur distribution. We find that RMT can dramatically increase the SNR of the prostate protocol, where the coefficient of variation of the RMT reconstruction for 1 average is lower than the conventional reconstruction of 14 averages. Thereby, RMT allows to reduce scan time by over 5-fold with comparable image quality.

This abstract and the presentation materials are available to 2020 meeting attendees and eLibrary customers only; a login is required.

Join Here