Four Dimensional MR Image Analysis of Dynamic Renography

A novel four dimensional image analysis approach including registration and segmentation of dynamic contrast enhanced renal MR images is presented. This integrated method is motivated by the observation of the reciprocity between registration and segmentation in 4D time-series images. Fully automated Fourier-based registration with sub-voxel accuracy and semi-automated time-series segmentation were intertwined to improve the accuracy in a multi-step fashion. We have tested our algorithm on several real patient data sets. Clinical validation showed remarkable and consistent agreement between the proposed method and manual segmentation by experts

[1]  José M. F. Moura,et al.  Kidney segmentation in MRI sequences using temporal dynamics , 2002, Proceedings IEEE International Symposium on Biomedical Imaging.

[2]  A. Hasman,et al.  MR renography by semiautomated image analysis: Performance in renal transplant recipients , 2001, Journal of magnetic resonance imaging : JMRI.

[3]  Jerry L. Prince,et al.  Snakes, shapes, and gradient vector flow , 1998, IEEE Trans. Image Process..

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

[5]  Peter L. Choyke,et al.  Registration of time-series contrast enhanced magnetic resonance images for renography , 2001, Proceedings 14th IEEE Symposium on Computer-Based Medical Systems. CBMS 2001.

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

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

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

[9]  Ting Song,et al.  Automatic 4-D Registration in Dynamic MR Renography , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.

[10]  José M. F. Moura,et al.  Subpixel registration in renal perfusion MR image sequence , 2004, 2004 2nd IEEE International Symposium on Biomedical Imaging: Nano to Macro (IEEE Cat No. 04EX821).

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

[12]  A. Kirsch,et al.  MR imaging of kidneys: functional evaluation using F-15 perfusion imaging , 2003, Pediatric Radiology.

[13]  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.

[14]  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.

[15]  Ravi Bansal,et al.  Segmentation of Dynamic N-D Data Sets via Graph Cuts Using Markov Models , 2001, MICCAI.

[16]  A. Farag,et al.  Automatic detection of renal rejection after kidney transplantation , 2005 .