Adaptive phase correction of diffusion-weighted images

NeuroImage

Guillaume Gilbert¹  Rachid Deriche²  Jean-Philippe Thiran³  Maxime Descoteaux⁴  Marco Pizzolato⁴ 

[1] Corresponding author.;Radiology Department, Centre Hospitalier Universitaire Vaudois and University of Lausanne, Lausanne, Switzerland;MR Clinical Science, Philips Healthcare Canada, Markham, ON, Canada;Signal Processing Lab (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland;

关键词: Phase correction;    Phase estimation;    Oriented laplacian;    Diffusion MRI;    Rician noise;   

DOI  :  

来源: DOAJ

【 摘 要 】

Phase correction (PC) is a preprocessing technique that exploits the phase of images acquired in Magnetic Resonance Imaging (MRI) to obtain real-valued images containing tissue contrast with additive Gaussian noise, as opposed to magnitude images which follow a non-Gaussian distribution, e.g. Rician. PC finds its natural application to diffusion-weighted images (DWIs) due to their inherent low signal-to-noise ratio and consequent non-Gaussianity that induces a signal overestimation bias that propagates to the calculated diffusion indices. PC effectiveness depends upon the quality of the phase estimation, which is often performed via a regularization procedure. We show that a suboptimal regularization can produce alterations of the true image contrast in the real-valued phase-corrected images. We propose adaptive phase correction (APC), a method where the phase is estimated by using MRI noise information to perform a complex-valued image regularization that accounts for the local variance of the noise. We show, on synthetic and acquired data, that APC leads to phase-corrected real-valued DWIs that present a reduced number of alterations and a reduced bias. The substantial absence of parameters for which human input is required favors a straightforward integration of APC in MRI processing pipelines.

【 授权许可】

Unknown