Non-iterative reconstruction with a prior for undersampled radial MRI data
نویسندگان
چکیده
This paper develops an FBP-MAP (Filtered Backprojection, Maximum a Posteriori) algorithm to reconstruct MRI images from under-sampled data. An objective function is first set up for the MRI reconstruction problem with a data fidelity term and a Bayesian term. The Bayesian term is a constraint in the temporal dimension. This objective function is minimized using the calculus of variations. The proposed algorithm is non-iterative. Undersampled dynamic myocardial perfusion MRI data were used to test the feasibility of the proposed technique. It is shown that the non-iterative Fourier reconstruction method effectively incorporates the temporal constraint and significantly reduces the angular aliasing artifacts caused by undersampling. A significant advantage of the proposed non-iterative Fourier technique over the iterative techniques is its fast computation time.
منابع مشابه
Undersampled radial MRI with multiple coils. Iterative image reconstruction using a total variation constraint.
The reconstruction of artifact-free images from radially encoded MRI acquisitions poses a difficult task for undersampled data sets, that is for a much lower number of spokes in k-space than data samples per spoke. Here, we developed an iterative reconstruction method for undersampled radial MRI which (i) is based on a nonlinear optimization, (ii) allows for the incorporation of prior knowledge...
متن کاملMagnetic Resonance in Medicine 57:1086–1098 (2007) Undersampled Radial MRI with Multiple Coils. Iterative Image Reconstruction Using a Total Variation Constraint
The reconstruction of artifact-free images from radially encoded MRI acquisitions poses a difficult task for undersampled data sets, that is for a much lower number of spokes in k-space than data samples per spoke. Here, we developed an iterative reconstruction method for undersampled radial MRI which (i) is based on a nonlinear optimization, (ii) allows for the incorporation of prior knowledge...
متن کامل3D Undersampled Golden-Radial Phase Encoding Using Iterative Reconstructions and Inherent Regularization
INTRODUCTION: The reconstruction of sensitivity–encoded non–Cartesian undersampled MRI has been facilitated by the use of iterative techniques [1]. However, the ill-conditioning of the associated inverse problem produces residual aliasing and noise amplification. A proven approach to stabilize the reconstruction and to diminish these effects is the use of explicit regularization methods [2-3], ...
متن کاملPocsense: Pocs-based Reconstruction for Sensitivity Encoded Mri
A novel method for iterative reconstruction of images from undersampled MRI data acquired by multiple receiver coil systems is presented. Based on parallel Projection onto Convex Sets (POCS) formalism, the method for SENSitivity Encoded data reconstruction (POCSENSE) can be readily modified to include various linear and non-linear reconstruction constraints. Such constraints may be beneficial f...
متن کاملHighly Undersampled 3D Golden Ratio Radial Imaging with Iterative Reconstruction
Introduction Compressed Sensing (CS) [1,2] suggests that using nonlinear reconstruction algorithms based on convex optimization an accurate signal reconstruction can be obtained from a number of samples much lower than required by the Nyquist limit. Recently, CS was demonstrated for MR imaging from undersampled data [3, 4]. Prerequisites for a good image reconstruction are the image compressibi...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- International journal of imaging systems and technology
دوره 23 1 شماره
صفحات -
تاریخ انتشار 2013