Segmentation-Driven Image Registration-Application to 4D DCE-MRI Recordings of the Moving Kidneys

Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) of the kidneys requires proper motion correction and segmentation to enable an estimation of glomerular filtration rate through pharmacokinetic modeling. Traditionally, co-registration, segmentation, and pharmacokinetic modeling have been applied sequentially as separate processing steps. In this paper, a combined 4D model for simultaneous registration and segmentation of the whole kidney is presented. To demonstrate the model in numerical experiments, we used normalized gradients as data term in the registration and a Mahalanobis distance from the time courses of the segmented regions to a training set for supervised segmentation. By applying this framework to an input consisting of 4D image time series, we conduct simultaneous motion correction and two-region segmentation into kidney and background. The potential of the new approach is demonstrated on real DCE-MRI data from ten healthy volunteers.

[1]  Nikos Paragios,et al.  Joint Tumor Segmentation and Dense Deformable Registration of Brain MR Images , 2012, MICCAI.

[2]  D Atkinson,et al.  Registration of dynamic contrast-enhanced MRI using a progressive principal component registration (PPCR) , 2007, Physics in medicine and biology.

[3]  Max A. Viergever,et al.  Image registration by maximization of combined mutual information and gradient information , 2000, IEEE Transactions on Medical Imaging.

[4]  Laurent Hermoye,et al.  Glomerular filtration rate: Assessment with dynamic contrast‐enhanced MRI and a cortical‐compartment model in the rabbit kidney , 2004, Journal of magnetic resonance imaging : JMRI.

[5]  Nobuhiko Hata,et al.  Impact of nonrigid motion correction technique on pixel‐wise pharmacokinetic analysis of free‐breathing pulmonary dynamic contrast‐enhanced MR imaging , 2011, Journal of magnetic resonance imaging : JMRI.

[6]  L. Schad,et al.  Assessment of kidney volumes from MRI: acquisition and segmentation techniques. , 2012, AJR. American journal of roentgenology.

[7]  A. Peters,et al.  Reproducibilities and responses to food intake of GFR measured with chromium-51-EDTA and iohexol simultaneously and independently in normal subjects. , 2008, Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association.

[8]  R. B. Potts.  Some generalized order-disorder transformations , 1952, Mathematical Proceedings of the Cambridge Philosophical Society.

[9]  William L. Briggs,et al.  A multigrid tutorial, Second Edition , 2000 .

[10]  Erlend Hodneland,et al.  Registration of Dynamic Contrast Enhanced MRI with Local Rigidity Constraint , 2012, WBIR.

[11]  Jens von Berg,et al.  A Communication Term for the Combined Registration and Segmentation , 2009 .

[12]  Erlend Hodneland,et al.  Normalized gradient fields and mutual information for motion correction of DCE-MRI images , 2013, 2013 8th International Symposium on Image and Signal Processing and Analysis (ISPA).

[13]  G. Wright,et al.  Rapid high‐resolution T1 mapping by variable flip angles: Accurate and precise measurements in the presence of radiofrequency field inhomogeneity , 2006, Magnetic resonance in medicine.

[14]  Benoit M Dawant,et al.  A nonrigid registration algorithm for longitudinal breast MR images and the analysis of breast tumor response. , 2009, Magnetic resonance imaging.

[15]  Dinggang Shen,et al.  Measuring temporal morphological changes robustly in brain MR images via 4-dimensional template warping , 2004, NeuroImage.

[16]  Aly A. Farag,et al.  Graph Cuts Framework for Kidney Segmentation with Prior Shape Constraints , 2007, MICCAI.

[17]  Albrecht Böttcher,et al.  $C^*$-Algebras in Numerical Analysis , 2000, Irish Mathematical Society Bulletin.

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

[19]  Luminita A. Vese,et al.  A combined segmentation and registration framework with a nonlinear elasticity smoother , 2009, Comput. Vis. Image Underst..

[20]  T. Chan,et al.  International Journal of C 2004 Institute for Scientific Numerical Analysis and Modeling Computing and Information a Survey on Multiple Level Set Methods with Applications for Identifying Piecewise Constant Functions , 2022 .

[21]  Anthony J. Yezzi,et al.  A variational framework for integrating segmentation and registration through active contours , 2003, Medical Image Anal..

[22]  Pratik Shah,et al.  Simultaneous Registration and Segmentation by L1 Minimization , 2012, MLMI.

[23]  Qing Yang,et al.  How accurate is dynamic contrast‐enhanced MRI in the assessment of renal glomerular filtration rate? A critical appraisal , 2008, Journal of magnetic resonance imaging : JMRI.

[24]  William L. Briggs,et al.  A multigrid tutorial , 1987 .

[25]  Tony F. Chan,et al.  Active contours without edges , 2001, IEEE Trans. Image Process..

[26]  Boudewijn P. F. Lelieveldt,et al.  Fully Automated Motion Correction in First-Pass Myocardial Perfusion MR Image Sequences , 2008, IEEE Transactions on Medical Imaging.

[27]  P. Mahalanobis.  On the generalized distance in statistics , 1936 .

[28]  Ganesh Adluru,et al.  Model‐based registration for dynamic cardiac perfusion MRI , 2006, Journal of magnetic resonance imaging : JMRI.

[29]  J. Modersitzki,et al.  Ill-posed medicine—an introduction to image registration , 2008 .

[30]  Maximilian F Reiser,et al.  MRI-Measurement of Perfusion and Glomerular Filtration in the Human Kidney With a Separable Compartment Model , 2008, Investigative radiology.

[31]  Roger Boyle,et al.  Mediated spatiotemporal fusion of multiple cardiac magnetic resonance datasets for patient-specific perfusion analysis , 2010, 2010 Computing in Cardiology.

[32]  Aly A. Farag,et al.  A kidney segmentation approach from DCE-MRI using level sets , 2008, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.

[33]  Henry Rusinek,et al.  Functional MRI of the kidneys , 2013, Journal of magnetic resonance imaging : JMRI.

[34]  S. McCormick,et al.  A multigrid tutorial (2nd ed.) , 2000 .

[35]  Erlend Hodneland,et al.  Normalized gradient fields for nonlinear motion correction of DCE-MRI time series , 2014, Comput. Medical Imaging Graph..

[36]  Jan Modersitzki,et al.  Numerical Methods for Image Registration , 2004 .

[37]  Heinz Handels,et al.  A Variational Approach for Combined Segmentation and Estimation of Respiratory Motion in Temporal Image Sequences , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[38]  T. Chan,et al.  Multiple level set methods with applications for identifying piecewise constant functions , 2004 .

[39]  Erlend Hodneland,et al.  A Unified Framework for Automated 3-D Segmentation of Surface-Stained Living Cells and a Comprehensive Segmentation Evaluation , 2009, IEEE Transactions on Medical Imaging.

[40]  Eldad Haber,et al.  Intensity Gradient Based Registration and Fusion of Multi-modal Images , 2006, MICCAI.

[41]  Francesco Sardanelli,et al.  Measurement of renal volume using respiratory-gated MRI in subjects without known kidney disease: intraobserver, interobserver, and interstudy reproducibility. , 2011, European journal of radiology.

[42]  Nassir Navab,et al.  Automatic alignment of renal DCE-MRI image series for improvement of quantitative tracer kinetic studies , 2008, SPIE Medical Imaging.

[43]  Angela Caunce,et al.  Tracer kinetic model–driven registration for dynamic contrast‐enhanced MRI time‐series data , 2007, Magnetic resonance in medicine.

[44]  L. Vese,et al.  A Variational Method in Image Recovery , 1997 .

[45]  N. Michoux,et al.  Analysis of contrast-enhanced MR images to assess renal function , 2006, Magnetic Resonance Materials in Physics, Biology and Medicine.

[46]  Arvid Lundervold,et al.  ssessment of 3 D DCE-MRI of the kidneys using non-rigid image registration nd segmentation of voxel time courses rank , 2009 .

[47]  Paul A. Viola,et al.  Alignment by Maximization of Mutual Information , 1997, International Journal of Computer Vision.

[48]  Tony F. Chan,et al.  Image processing and analysis - variational, PDE, wavelet, and stochastic methods , 2005 .

[49]  Guy Marchal,et al.  Multimodality image registration by maximization of mutual information , 1997, IEEE Transactions on Medical Imaging.

[50]  Michael Brady,et al.  Analysis of dynamic MR breast images using a model of contrast enhancement , 1997, Medical Image Anal..

[51]  S. Sourbron.  Technical aspects of MR perfusion. , 2010, European journal of radiology.

[52]  Mark W. Woolrich,et al.  Advances in functional and structural MR image analysis and implementation as FSL , 2004, NeuroImage.

[53]  Erlend Hodneland,et al.  In vivo estimation of glomerular filtration in the kidney using DCE-MRI , 2011, 2011 7th International Symposium on Image and Signal Processing and Analysis (ISPA).

[54]  Jan Modersitzki,et al.  FAIR: Flexible Algorithms for Image Registration , 2009 .

[55]  Stephen T. C. Wong,et al.  oint registration and segmentation of serial lung CT images for image-guided ung cancer diagnosis and therapy , 2009 .

[56]  Ayman El-Baz,et al.  Image Analysis of Renal DCE MRI for the Detection of Acute Renal Rejection , 2006, 18th International Conference on Pattern Recognition (ICPR'06).

[57]  Christopher J. Taylor,et al.  A non-linear registration method for DCE-MRI and DCE-CT comparison in bladder tumors , 2008, 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[58]  P. Nilsson-ehle,et al.  Plasma clearance of a new contrast agent, iohexol: a method for the assessment of glomerular filtration rate. , 1984, The Journal of laboratory and clinical medicine.

[59]  Edward Lin,et al.  Determinants and functional significance of renal parenchymal volume in adults. , 2011, Clinical journal of the American Society of Nephrology : CJASN.