IEEE transactions on medical imaging
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IEEE Trans Med Imaging · Aug 2007
A maximum likelihood approach to parallel imaging with coil sensitivity noise.
Parallel imaging is a powerful technique to speed up magnetic resonance (MR) image acquisition via multiple coils. Both the received signal of each coil and its sensitivity map, which describes its spatial response, are needed during reconstruction. Widely used schemes such as SENSE assume that sensitivity maps of the coils are noiseless while the only errors are in coil outputs. ⋯ In this paper, we take a maximum likelihood approach to the problem of parallel imaging in the presence of independent Gaussian sensitivity noise. This results in a quasi-quadratic objective function, which can be efficiently minimized. Experimental evidence suggests substantial gains over conventional SENSE, especially in nonideal imaging conditions like low signal-to-noise ratio (SNR), high g-factors and large acceleration, using sensitivity maps suffering from misalignment, ringing, and random noise.
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IEEE Trans Med Imaging · Aug 2007
Comparative StudyEffect of spatial alignment transformations in PCA and ICA of functional neuroimages.
It has been previously observed that independent component analysis (ICA), if applied to data pooled in a particular way, may lessen the need for spatial alignment of scans in a functional neuroimaging study. In this paper, we seek to determine analytically the conditions under which this observation is true, not only for spatial ICA, but also for temporal ICA and for principal component analysis (PCA). ⋯ We illustrate our findings using functional magnetic-resonance imaging (fMRI) data. Our analysis is applicable to both intersubject and intrasubject spatial normalization.
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The purpose of this work was to present and evaluate a new method for directly designing T2-selective preparation pulses. Using a modified Shinnar-Le-Roux (SLR) transform, the design of T2-selective pulses becomes equivalent to designing a pair of polynomials one of which represents the longitudinal magnetization and the other the transverse magnetization. The polynomials enable one to directly analyze the various tradeoffs involved in the design. ⋯ Phantom scans showed good signal suppression of long-T2 species. This is supported by good long-T2 signal suppression seen on the in vivo images. Simulations indicate that the pulse is robust to +/-150 Hz B0 inhomogeneities and +/-10% B1 inhomogeneities.
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IEEE Trans Med Imaging · Jul 2007
BSLIM: spectral localization by imaging with explicit B0 field inhomogeneity compensation.
Magnetic resonance spectroscopy imaging (MRSI) is an attractive tool for medical imaging. However, its practical use is often limited by the intrinsic low spatial resolution and long acquisition time. Spectral localization by imaging (SLIM) has been proposed as a non-Fourier reconstruction algorithm that incorporates spatial a priori information about spectroscopically uniform compartments. ⋯ A B0-field inhomogeneity map, which can be acquired rapidly and at high resolution, is used by the new algorithm as additional a priori information. We show that the proposed method is distinct from the generalized SLIM (GSLIM) framework. Experimental results of a two-compartment phantom demonstrate the feasibility of the method and the importance of inhomogeneity compensation.
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IEEE Trans Med Imaging · Jul 2007
Accelerating dynamic spiral MRI by algebraic reconstruction from undersampled k--t space.
The temporal resolution of dynamic magnetic resonance imaging (MRI) can be increased by sampling a fraction of k-space in an interleaved fashion, which introduces spatial and temporal aliasing. We describe algebraically and graphically the aliasing process caused by dynamic undersampled spiral imaging within 3-D xyf space (the Fourier transform of k(x)k(y)t space) and formulate the unaliasing problem as a set of independent linear inversions. ⋯ Numerical simulation and in vivo experiments using spiral twofold undersampling demonstrate reduced motion artifacts and the improved depiction of fine cardiac structures. The achieved reduction of motion artifacts and motion blur is comparable to simple filtering, which is computationally more efficient, while the proposed algebraic framework offers greater flexibility to incorporate additional algebraic acceleration techniques and to handle arbitrary sampling schemes.