Name
Title | ||
|---|---|---|
Modeling anisotropic undersampling of magnetic resonance angiographies and reconstruction of a high-resolution isotropic volume using half-quadratic regularization techniques |
Abstract | ||
|---|---|---|
In this paper we address the problem of reconstructing a high resolution volumic image from several low resolution data sets. A solution to this problem is proposed in the particular framework of magnetic resonance angiography (MRA), where the resolution is limited by a trade-off between the spatial resolution and the acquisition time, both being proportional to the number of samples acquired in k-space. For this purpose only the meaningful spatial frequencies of the 3D k-space of the vessel are acquired, which is achieved using successive acquisitions with decreased spatial resolution, leading to highly anisotropic data sets in one or two specific directions. The reconstruction of the MRA volume from these data sets relies on an edge-preserving regularization method and leads to two different implementations: the first one is based on a conjugate gradient algorithm, and the second one on half-quadratic developments. The hyper parameters of the method were experimentally determined using a set of simulated data, and promising results were obtained on aorta and carotid artery acquisitions, where on the one hand a good fidelity to the acquired data is maintained, and on the other hand homogeneous areas are smooth and edges are well preserved. Half-quadratic regularization proved to be particularly well adapted to the MRA problem and leads to a fast iterative algorithm requiring only scalar and FFT computations. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1016/j.sigpro.2003.12.013 | Signal Processing |
Keywords | Field | DocType |
magnetic resonance angiography,simulated data,anisotropic data set,meaningful spatial frequency,edge-preserving regularization,mra problem,acquired data,high resolution volumic image,high-resolution isotropic volume,spatial resolution,half-quadratic regularization technique,anisotropic undersampling,magnetic resonance angiographies,high-resolution,undersampling,half-quadratic regularization,low resolution data set,mra volume,conjugate gradient,iterative algorithm,low resolution,high resolution,spatial frequency | Conjugate gradient method,Iterative reconstruction,Mathematical optimization,Iterative method,Image processing,Undersampling,Regularization (mathematics),Fast Fourier transform,Image resolution,Mathematics | Journal |
Volume | Issue | ISSN |
84 | 4 | Signal Processing |
Citations | PageRank | References |
2 | 0.45 | 11 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Elodie Roullot | 1 | 10 | 2.99 |
| Alain Herment | 2 | 12 | 4.65 |
| Isabelle Bloch | 3 | 20 | 3.08 |
| Alain De Cesare | 4 | 7 | 4.97 |
| Mila Nikolova | 5 | 1792 | 105.71 |
| Élie Mousseaux | 6 | 14 | 5.73 |