Automatic 4-D Registration in Dynamic MR Renography.

Dynamic contrast-enhanced 4-D MR renography has the potential for broad clinical applications, but suffers from respiratory motion that limits analysis and interpretation. Since each examination yields at least over 10 - 20 serial 3-D images of the abdomen, manual registration is prohibitively labor-intensive. Besides in-plane motion and translation, out-of-plane motion and rotation are observed in the image series. In this paper, a novel robust and automated technique for removing out-of-plane translation and rotation with sub-voxel accuracy in 4-D dynamic MR images is presented. The method was evaluated on simulated motion data derived directly from a clinical patients data. The method was also tested on 24 clinical patient kidney data sets. Registration results were compared with a mutual information method, in which differences between manually co-registered time-intensity curves and tested time-intensity curves were compared. Evaluation results showed that our method agreed well with these ground truth data.

[1]  Max A. Viergever,et al.  Efficient and reliable schemes for nonlinear diffusion filtering , 1998, IEEE Trans. Image Process..

[2]  D. Shanno.  Conditioning of Quasi-Newton Methods for Function Minimization , 1970 .

[3]  Guido Gerig,et al.  Nonlinear anisotropic filtering of MRI data , 1992, IEEE Trans. Medical Imaging.

[4]  Bo Tao,et al.  Analysis of image registration noise due to rotationally dependent aliasing , 2003, J. Vis. Commun. Image Represent..

[5]  Elsa D. Angelini,et al.  Assessment of visual quality and spatial accuracy of fast anisotropic diffusion and scan conversion algorithms for real-time three-dimensional spherical ultrasound , 2004, SPIE Medical Imaging.

[6]  J. Maintz.  Retrospective registration of tomographic brain images , 1996 .

[7]  Johan Montagnat,et al.  Anisotropic filtering for model-based segmentation of 4D cylindrical echocardiographic images , 2003, Pattern Recognit. Lett..

[8]  Michael T. Orchard,et al.  A fast direct Fourier-based algorithm for subpixel registration of images , 2001, IEEE Trans. Geosci. Remote. Sens..

[9]  Amir Averbuch,et al.  Pseudopolar-based estimation of large translations, rotations, and scalings in images , 2005, IEEE Trans. Image Process..

[10]  A Hasman,et al.  Movement correction of the kidney in dynamic MRI scans using FFT phase difference movement detection , 2001, Journal of magnetic resonance imaging : JMRI.

[11]  José M. F. Moura,et al.  Integrated registration of dynamic renal perfusion MR images , 2004, 2004 International Conference on Image Processing, 2004. ICIP '04..

[12]  Luca Lucchese,et al.  A Frequency Domain Technique for Range Data Registration , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[13]  Henry Rusinek,et al.  Dynamic three-dimensional MR renography for the measurement of single kidney function: initial experience. , 2003, Radiology.

[14]  R Kikinis,et al.  Semiautomated ROI analysis in dynamic MR studies. Part I: Image analysis tools for automatic correction of organ displacements. , 1991, Journal of computer assisted tomography.