Dynamic Contrast-Enhanced Magnetic Resonance Images of the Kidney

In this article, an improved method to segment the renal cortex and medulla and to eliminate the influence of kidney motion produced by respiration is proposed. On the basis of an adaptive threshold estimated from the mean gray levels of the grown regions, a region-growing algorithm is presented to produce a three-dimensional (3-D) kidney contour and to segment the renal structures. Moreover, a shell mask of kidney margin is proposed to realize a coarse matching so as to eliminate the image translation, which makes the processing simple and direct in spatial processing without any image transform computations, and a correlation computation can be implemented with great efficiency. Then, a refined matching with a mask of cortex is completed through a 3-D correlation algorithm to ensure the accurate registration of the images in different phases. Comparing with the global mask including the whole kidney, both the shell mask and the cortex mask significantly contribute to decreasing the matching errors for images with nonuniform intensity signals, which much improves the registration quality of renal MR images. In this way, the effect of the respiration motions can be eliminated so that the intensity measurement in different phases becomes accurate within the respective structures.

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

[2]  A Hasman,et al.  Reduction of noise in medullary renograms from dynamic MR images , 2000, Journal of magnetic resonance imaging : JMRI.

[3]  Jing Fang,et al.  Nanoscale in-plane displacement evaluation by AFM scanning and digital image correlation processing , 2005 .

[4]  Rolf Adams,et al.  Seeded Region Growing , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  F Stacul,et al.  [Morpho-functional study of the kidney in patients with kidney disease and liver disease with magnetic resonance]. , 1998, La Radiologia medica.

[6]  Ting Song,et al.  Automatic 4-D Registration in Dynamic MR Renography. , 2005, Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference.

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

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