Faculty Bibliography

The required time of conventional magnetic resonance spectroscopic imaging technique is too long to be applied to clinic. It is necessary to develop the fast methods for magnetic resonance spectroscopic imaging. Nowadays there are 7 kinds of methods presented, which come from MRI techniques. In this contribution the conventional spectroscopic imaging and 7 sorts of fast spectroscopic imaging are elaborated. It is envisaged that more rapid imaging techniques will be designed, if these arbitrary trajectory reconstruction methods in MRI are applied to spectroscopic imaging.

A PC-based software was developed and programmed with VC++6 for reconstructing MR images from the data acquired on an irregular k-space trajectory. It can read clinical MRI raw data and image data, create numerical phantoms, design k-space trajectories, generate k-space data from numerical phantom, calculate weighting functions, reconstruct images, and carry out error analysis for the reconstructed images. It is helpful to the investigations of new k-space trajectories and new reconstruction algorithms.

A sampling density compensation function denoted "same-image (SI) weight" is proposed to reconstruct MR images from the data acquired on an arbitrary k-space trajectory. An equation for the SI weight is established on the SI criterion and an iterative scheme is developed to find the weight. The SI weight is then used to reconstruct images from the data calculated on a random trajectory in a numerical phantom case and from the data acquired on interleaved spirals in an in vivo experiment, respectively. In addition, Pipe and Menon's weight (MRM 1999;41:179-186) is also used in the reconstructions to make a comparison. The images obtained with the SI weight were found to be slightly more accurate than those obtained with Pipe's weight.

The equal-phase line (EPL) algorithm is proposed as a means of allowing rapid Fourier transform (FT) reconstruction of MR image data acquired on a non-Cartesian grid. The pixels on the image are grouped according to their positions. The pixels in a group have the same phase in the complex exponential function -exp[j2pi(xu + yv)] and receive the same contribution from a data point. Each group is related to an EPL in the image space. The contribution of a data point can then be distributed to the pixels along the EPLs. The described EPL algorithm enables a decrease of the reconstruction time to about 40% of the direct FT (DrFT) for the non-Cartesian data. A numerical phantom and two sets of in vivo spiral data were used to investigate an optimal number of the EPLs and to measure the reconstruction time. The EPL algorithm runs nearly as fast as the look-up table (LUT) method (Dale et al. IEEE Trans Med Imaging 2001;20:207-217), but it does not require a large memory to store the coefficients in advance, as is required in the LUT method. Thus, the EPL algorithm can be used to reconstruct images up to 512 x 512 pixels in size in a PC of limited memory, and may be more conveniently applied to a multiprocessor system.