Diffusion MRI (dMRI) provides invaluable information for the study of tissue microstructure
and brain connectivity, but suffers from a range of imaging artifacts that greatly challenge the …

Over the past several years, although the resolution, signal-to-noise ratio and acquisition
speed of magnetic resonance imaging (MRI) technology have been increased, MR images …

Diffusion-weighted MRI (DW-MRI) has been increasingly used in imaging neuroscience
over the last decade. An early form of this technique, diffusion tensor imaging (DTI) was …

We present an extension of the BM3D filter to volumetric data. The proposed algorithm,
BM4D, implements the grou** and collaborative filtering paradigm, where mutually similar …

Purpose: To adapt the so‐called nonlocal means filter to deal with magnetic resonance (MR)
images with spatially varying noise levels (for both Gaussian and Rician distributed noise) …

Quantitative magnetic resonance analysis often requires accurate, robust, and reliable
automatic extraction of anatomical structures. Recently, template-war** methods …

Abstract Structure-preserved denoising of 3D magnetic resonance imaging (MRI) images is
a critical step in medical image analysis. Over the past few years, many algorithms with …

The search for efficient image denoising methods is still a valid challenge at the crossing of
functional analysis and statistics. In spite of the sophistication of the recently proposed …

Magnetic Resonance Imaging (MRI) is an essential medical imaging modality that provides
excellent soft-tissue contrast and high-resolution images of the human body, allowing us to …

This paper proposes two new methods for the three-dimensional denoising of magnetic
resonance images that exploit the sparseness and self-similarity properties of the images …