RF-Inhomogeneity Correction (aka bias) artifact is an important research field in Magnetic Resonance Imaging (MRI). Bias corrupts MR images altering their illumination even though they are acquired with the most recent scanners. Homomorphic Unsharp Masking (HUM) is a filtering technique aimed at correcting illumination inhomogeneity, but it produces a halo around the edges as a side effect. In ...

INTRODUCTION: Manganese Enhanced Magnetic Resonance Imaging (MEMRI) has been successfully used in the visualization of the hippocampal mossy fiber networks in the rat brain1. Although the hyperintensity of mossy fiber in the T1weighted image can be delineated manually, automatic segmentation is often difficult in the presence of varying signal intensity across the image caused by small surface ...

Introduction: In functional MRI (fMRI), the presence of subject motion during the acquisition of an image series can confound results. In general practice, only the magnitude portion of the images is used in the functional analysis [1], and thus correction for subject motion is required in only the magnitude images. However, statistical models for performing complex-valued fMRI analysis are ava...

PURPOSE A ghost correction strategy for Simultaneous Multi-Slice (SMS) EPI methods that provides improved ghosting artifact reduction compared to conventional methods is presented. Conventional Nyquist ghost correction methods for SMS-EPI rely on navigator data that contain phase errors from all slices in the simultaneously acquired slice-group. These navigator data may contain spatially nonlin...

A novel locally statistical active contour model (ACM) for image segmentation in the presence of intensity inhomogeneity is presented in this paper. The inhomogeneous objects are modeled as Gaussian distributions of different means and variances, and a moving window is used to map the original image into another domain, where the intensity distributions of inhomogeneous objects are still Gaussi...