Image analysis – Applications – Biomedical applications
Reexamination Certificate
2011-03-08
2011-03-08
Azarian, Seyed (Department: 2624)
Image analysis
Applications
Biomedical applications
C382S280000, C600S410000
Reexamination Certificate
active
07903858
ABSTRACT:
A set of image-space data is reconstructed from a set of k-space data. The set of image-space data is generated by minimizing a cost functional by an iterative non-linear conjugate gradient process. The iterative process may be accelerated by introducing k-space weighting to the cost functional. With proper choice of k-space weighting, a block-Toeplitz matrix is generated which permits use of Fast Fourier Transform techniques. An image is rendered from the set of image-space data.
REFERENCES:
patent: 6853191 (2005-02-01), Miller et al.
patent: 7076091 (2006-07-01), Rosenfeld
patent: 7418287 (2008-08-01), Tsao et al.
patent: 7439739 (2008-10-01), Beatty
patent: 7592809 (2009-09-01), King et al.
patent: 7634119 (2009-12-01), Tsougarakis et al.
T-C. Chang, et al., “MR Image Reconstruction from Sparse Radial Samples Using Bregman Iteration”, Proc. of Annual Meeting of ISMRM, Seattle, WA, USA, May 2006.
J.A. Fessler, et al., “Conjugate-Gradient Preconditioning Methods for Shift-Variant PET Image Reconstruction”, IEEE Transactions on Image Processing, vol. 8, No. 5, 1999.
J.A. Fessler, et al., “Toeplitz-Based Iterative Image Reconstruction for MRI with Correction for Magnetic Field Inhomogeneity”, IEEE Trans. on Signal Proces., 53(9), 2005.
Q.H. Liu, et al., “Iterative Algorithm for Nonuniform Inverse Fast Fourier Transform (NU-IFFT)”, Electronics Letters, vol. 34, No. 20, Oct. 1, 1998.
J.G. Pipe, “Reconstructing MR Images from Undersampled Data: Data-Weighting Considerations”, Magnetic Resonance in Medicine 43, 2000.
J.G. Pipe, et al., “Sampling Density Compensation in MRI: Rationale and an Iterative Numerical Solution”, Magnetic Resonance in Medicine 41, 1999.
J.R. Shewchuk, “An Introduction to the Conjugate Gradient Method without the Agonizing Pain”, Carnegie Mellon University, Pittsburgh, PA, 1994.
R. Van De Walle, et al., “Reconstruction of MR Images from Data Acquired on a General Nonregular Grid by Pseudoinverse Calculation”, IEEE Trans. on Med. Imaging, 19(12), 2000.
Chang Ti-chiun
Fang Tong
Müller Edgar
Song Jiayu
Speier Peter
Azarian Seyed
Siemens Aktiengesellschaft
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