A dual image approach for bias field correction in magnetic resonance imaging.

In this paper, we propose a dual image approach to correcting intensity inhomogeneities for MR images acquired using surface coils. Previous methods are usually not satisfactory due to restricted application domains, considerable human interactions, or some undesirable artifacts. The proposed algorithm provides nice correction results for a variety of surface-coil MR images. It is accomplished by using an additional body-coil MR image of a smaller size captured at the same position as that of the surface-coil image to facilitate the estimation of the bias field function. The correction algorithm consists of aligning the surface-coil image with the body-coil image and fitting a spline surface from a sparse set of data points for the associated bias field function. Experiments on some real images show satisfactory correction results by using the proposed algorithm.

[1]  Shang-Hong Lai,et al.  A new variational shape-from-orientation approach to correcting intensity inhomogeneities in magnetic resonance images , 1999, Medical Image Anal..

[2]  Benoit M. Dawant,et al.  Correction of intensity variations in MR images for computer-aided tissue classification , 1993, IEEE Trans. Medical Imaging.

[3]  R. Gupta,et al.  Polynomial modeling and reduction of RF body coil spatial inhomogeneity in MRI , 1993, IEEE Trans. Medical Imaging.

[4]  Shang-Hong Lai,et al.  Reliable and Efficient Computation of Optical Flow , 1998, International Journal of Computer Vision.

[5]  Gene H. Golub,et al.  Matrix computations , 1983 .

[6]  John E. Dennis,et al.  Numerical methods for unconstrained optimization and nonlinear equations , 1983, Prentice Hall series in computational mathematics.

[7]  B. Condon,et al.  Image non-uniformity in magnetic resonance imaging: its magnitude and methods for its correction. , 1987, The British journal of radiology.

[8]  G. Barker,et al.  Correction of intensity nonuniformity in MR images of any orientation. , 1993, Magnetic resonance imaging.

[9]  Charles R. Meyer,et al.  Retrospective correction of intensity inhomogeneities in MRI , 1995, IEEE Trans. Medical Imaging.

[10]  Shang-Hong Lai,et al.  A new variational shape-from-orientation approach to correcting intensity inhomogeneities in MR images , 1998, Proceedings. Workshop on Biomedical Image Analysis (Cat. No.98EX162).

[11]  Shang-Hong Lai,et al.  Robust and efficient image alignment with spatially varying illumination models , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[12]  M. Stella Atkins,et al.  Segmentation of multiple sclerosis lesions in intensity corrected multispectral MRI , 1996, IEEE Trans. Medical Imaging.