A joint estimation method for two-point water/fat imaging with regularized field map
نویسندگان
چکیده
INTRODUCTION A recently developed joint estimation method for water/fat separation, based on a penalized maximum likelihood (PML) formulation and graph cuts optimization, is able to perform robustly in the presence of large B0 field inhomogeneities [1]. This method requires the acquisition of at least three images with different TE shifts, because the water and fat components of the signal are allowed to have different initial phases [2]. However, 2-point methods can be advantageous in terms of acquisition time [3,4,5]. In this work, we adapt the joint estimation framework for 2-point acquisitions and demonstrate its performance using simulations, phantom results and in vivo data.
منابع مشابه
JIGSAW: Joint Inhomogeneity Estimation via Global Segment Assembly for Water-Fat Separation
Water-fat separation in magnetic resonance imaging (MRI) is of great clinical importance, and the key to uniform water-fat separation lies in field map estimation. This work deals with three-point field map estimation, in which water and fat are modelled as two single-peak spectral lines, and field inhomogeneities shift the spectrum by an unknown amount. Due to the simplified spectrum modelling...
متن کاملField-Corrected Imaging using Joint Estimation of Image and Field Map
1 Abstract In order to reduce acquisition time in dynamic scans, while still correcting for field inhomogeneities, an image reconstruction method is introduced that simultaneously estimates field-corrected images and their associated field maps while acquiring only part of k-space at each readout. A two-shot variable density spiral sequence is combined with a regularized nonlinear least-squares...
متن کاملGeneral Phase Regularized Reconstruction using Phase Cycling
PURPOSE To develop a general phase regularized image reconstruction method, with applications to partial Fourier imaging, water-fat imaging and flow imaging. THEORY AND METHODS The problem of enforcing phase constraints in reconstruction was studied under a regularized inverse problem framework. A general phase regularized reconstruction algorithm was proposed to enable various joint reconstr...
متن کاملRobust Phase Unwraping Using Grid-fit Method
In MRI, field map estimation techniques using 3 point multi-echo acquisitions have been developed for reliable water fat separation. Among the various techniques, Iterative Decomposition of water and fat with Echo Asymmetry and Leastsquares estimation (IDEAL) has gained considerable popularity as a iterative method for acquiring high quality water and fat images. A core of IDEAL is to have an i...
متن کاملRetrieving Three Dimensional Displacements of InSAR Through Regularized Least Squares Variance Component Estimation
Measuring the 3D displacement fields provide essential information regarding the Earth crust interaction and the mantle rheology. The interferometric synthetic aperture radar (InSAR) has an appropriate capability in revealing the displacements of the Earth’s crust. Although, it measures the real 3D displacements in the line of sight (LOS) direction. The 3D displacement vectors can be retrieved ...
متن کامل