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ABSTRACT: Recent advances in high field magnetic resonance technology have increased the interest in the phase of the complex data. Processed phase images are derived from the phase signal by removing the bias field and phase wraps from the initial data. However, the usefulness of this data has been hindered by artifacts at the brain/non-brain surface, particularly in cortical regions. A method is proposed that efficiently removes surface artifacts by performing Gaussian filtering with spatially varying parameters of unwrapped or complex filtered phase images. The proposed method is shown to produce improved images, revealing underlying structure and detail that are otherwise obscured by surface artifacts in images produced by traditional phase processing methods. Magn Reson Med 66:784-793, 2011. © 2011 Wiley-Liss, Inc.
Magnetic Resonance in Medicine 09/2011; 66(3):spcone. · 2.96 Impact Factor
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ABSTRACT: Oversampled filter banks (FBs) with lattice structure allow fast implementation and guarantee the linear phase and perfect reconstruction property. For such FBs, the synthesis FB is not unique. This nonuniqueness provides extra design freedom for optimal reduction of subband noise required in many applications. However, the existing design methods of synthesis FB for optimal reduction of subband noise cannot guarantee the linear phase and lattice structure property. This paper studies the design of oversampled synthesis FBs with guaranteed lattice structure for optimal reduction of subband noise. Based on a state space parameterization of all synthesis FBs with lattice structure, the explicit formulae are derived to find the optimal solution for noise reduction. Numerical examples are presented to demonstrate the effectiveness of the new design methods obtained.
IEEE Transactions on Signal Processing 09/2011; · 2.63 Impact Factor
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[show abstract]
[hide abstract]
ABSTRACT: Recent advances in high field magnetic resonance technology have increased the interest in the phase of the complex data. Processed phase images are derived from the phase signal by removing the bias field and phase wraps from the initial data. However, the usefulness of this data has been hindered by artifacts at the brain/non-brain surface, particularly in cortical regions. A method is proposed that efficiently removes surface artifacts by performing Gaussian filtering with spatially varying parameters of unwrapped or complex filtered phase images. The proposed method is shown to produce improved images, revealing underlying structure and detail that are otherwise obscured by surface artifacts in images produced by traditional phase processing methods.
Magnetic Resonance in Medicine 03/2011; 66(3):784-93. · 2.96 Impact Factor
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IEEE Transactions on Signal Processing. 01/2011; 59:3549-3559.
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IEEE Transactions on Signal Processing. 01/2011; 59:5830-5841.
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Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011, May 22-27, 2011, Prague Congress Center, Prague, Czech Republic; 01/2011
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Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011, May 22-27, 2011, Prague Congress Center, Prague, Czech Republic; 01/2011
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ABSTRACT: This paper investigates and solves the problem of frame bound ratio minimization for oversampled perfect reconstruction (PR) filter banks (FBs). For a given analysis PRFB, a finite dimensional convex optimization algorithm is derived to redesign the subband gain of each channel. The redesign minimizes the frame bound ratio of the FB while maintaining its original properties and performance. The obtained solution is precise without involving frequency domain approximation and can be applied to many practical problems in signal processing. The optimal solution is applied to subband noise suppression and tree structured FB gain optimization, resulting in deeper insights and novel solutions to these two general classes of problems and considerable performance improvement. Effectiveness of the optimal solution is demonstrated by extensive numerical examples.
IEEE Transactions on Signal Processing 02/2010; · 2.63 Impact Factor
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ABSTRACT: This paper investigates optimal signal predictive quantization in the presence of source model uncertainties. It uses polytopic system model to represent the uncertainties in source signal and uses the recent results on robust filtering to obtain a robust H<sub>∞</sub> optimal design of signal predictor. Results of computational study is presented to demonstrate the advantages of the obtained design.
Decision and Control, 2009 held jointly with the 2009 28th Chinese Control Conference. CDC/CCC 2009. Proceedings of the 48th IEEE Conference on; 01/2010
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ABSTRACT: Accelerated parallel MRI has been widely used in medical research and clinical diagnoses. This paper presents a two dimensional (2D) infinite impulse response (IIR) model of inverse filter to replace the finite impulse response model currently used in GRAPPA class image reconstruction methods. The IIR model better characterizes the correlation of k-space data points and better approximates the inversion of parallel imaging process. The experiments on in vivo accelerated cardiac imaging show that the proposed method significantly reduces reconstruction errors compared with conventional 2D GRAPPA method, particularly at the high acceleration rates.
Control and Automation, 2009. ICCA 2009. IEEE International Conference on; 01/2010
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IEEE Transactions on Signal Processing. 01/2010; 58:209-220.
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Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010, 14-19 March 2010, Sheraton Dallas Hotel, Dallas, Texas, USA; 01/2010
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ABSTRACT: This paper studies the optimal noise reduction problem for oversampled filter banks (FBs) with perfect reconstruction (PR) constraint. Both the optimal design and worst case design are considered, where the former caters for the noise with known power spectral density (PSD) and the latter for the noise with unknown PSD. State-space based explicit formulae involving only algebraic Riccati equation and matrix manipulations are provided for the general (IIR or FIR) oversampled PR FBs, and the relations between different cases are analyzed and revealed. Extensive numerical examples are provided to illustrate the proposed design methods and to show their effectiveness.
IEEE Transactions on Signal Processing 11/2009; · 2.63 Impact Factor
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ABSTRACT: Accelerated parallel MRI has advantage in imaging speed, and its image quality has been improved continuously in recent years. This paper introduces a two-dimensional infinite impulse response model of inverse filter to replace the finite impulse response model currently used in generalized autocalibrating partially parallel acquisitions class image reconstruction methods. The infinite impulse response model better characterizes the correlation of k-space data points and better approximates the perfect inversion of parallel imaging process, resulting in a novel generalized image reconstruction method for accelerated parallel MRI. This k-space-based reconstruction method includes the conventional generalized autocalibrating partially parallel acquisitions class methods as special cases and has a new infinite impulse response data estimation mechanism for effective improvement of image quality. The experiments on in vivo MRI data show that the proposed method significantly reduces reconstruction errors compared with the conventional two-dimensional generalized autocalibrating partially parallel acquisitions method, particularly at the high acceleration rates.
Magnetic Resonance in Medicine 10/2009; 63(2):502-9. · 2.96 Impact Factor
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ABSTRACT: For an oversampled linear phase (LP) perfect reconstruction filter banks with lattice structure, the synthesis FB is not unique. However, existing methods to choose a synthesis FB for ldquooptimalrdquo noise reduction may destroy the linear phase and lattice structure property. This paper studies the noise reduction design problem for oversampled filter banks (FBs) preserving lattice structure. Both the optimal design and worst case design are considered, where the former caters for the noise with known power spectral density (PSD), and the latter for the noise with unknown PSD. Explicit formula for the former and LMI-based algorithms for the latter are provided.
Asian Control Conference, 2009. ASCC 2009. 7th; 09/2009
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ABSTRACT: The length of scan time is a critical issue in Magnetic Resonance Imaging(MRI). Parallel MRI techniques have recently been introduced to shorten the scanning time by using multiple receiver coils to acquire the MR signal. As a result, the imaging process is accelerated several times compared to conventional non-accelerated MRI. In this paper, we provide a new reconstruction method for parallel MRI that improves the resultant image quality. Our algorithm involves the combination of two popular and commercially utilised parallel MRI reconstruction techniques, SENSE and GRAPPA. These two methods are complementary to each other, and are traditionally implemented in different imaging conditions. Our proposed method, called the SG reconstruction method, takes advantage of the distinct merits of both SENSE and GRAPPA to improve the image reconstruction quality. We demonstrate the superiority of the SG algorithm through comparison to SENSE and GRAPPA applied to high-field, experimental MRI data.
Computing: Techniques and Applications, 2008. DICTA '08.Digital Image; 01/2009
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IEEE Transactions on Signal Processing. 01/2009; 57:3844-3857.
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Conference Proceeding:
Robust H
Proceedings of the 48th IEEE Conference on Decision and Control, CDC 2009, combined withe the 28th Chinese Control Conference, December 16-18, 2009, Shanghai, China; 01/2009
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ABSTRACT: Incorporation of parallel imaging technique in dynamic magnetic resonance imaging process accelerates significantly the imaging speed. The acceleration is achieved by acquiring the k-space data sparsely in each frame. To unwrap the aliased images caused by the k-space under-sampling, the reconstruction algorithms need the local sensitivity variation, the sensitivity map, of the receiving coils. Current estimation methods are unable to provide the true sensitivity map, and the calibration errors in the estimated sensitivity map can dramatically increase the image artifacts. This paper introduces a novel two-dimensional k-t modeling approach to improve the estimation of sensitivity map. A 2D model is fitted to each k-t plane and is updated for each estimated data point. The model is used to estimate the unacquired k-space data in each frame. A full k-t plane is composed using the estimated and acquired datasets and is used to obtain improved estimation of sensitivity map. Experiments on real dynamic parallel MRI data demonstrate that the proposed method significantly improve the quality of reconstructed MR images.
Engineering in Medicine and Biology Society, 2008. EMBS 2008. 30th Annual International Conference of the IEEE; 09/2008
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ABSTRACT: A causal realization of an inverse system can be unstable and an anti-casual realization is to deal with this problem to provide a numerically stable procedure to inverse the system and compute its input signal. In this paper, we consider the anti-causal realization of the inverse of discrete time linear periodic systems obtained by an outer-inner factorization approach. It is shown that the outer-inner factorization can result in a stable anti-causal realization. An expression of the inversion error is derived, showing such an error is inevitable due to the anti-causal reversal operation.
Control and Decision Conference, 2008. CCDC 2008. Chinese; 08/2008
