A combined segmentation and registration framework with a nonlinear elasticity smoother

[1]  M. Powell.  A method for nonlinear constraints in minimization problems , 1969 .

[2]  M. Hestenes.  Multiplier and gradient methods , 1969 .

[3]  R. C. Thompson,et al.  On the Eigenvalues of Sums of Hermitian Matrices , 1971 .

[4]  R. Tyrrell Rockafellar,et al.  A dual approach to solving nonlinear programming problems by unconstrained optimization , 1973, Math. Program..

[5]  J. Ball.  Convexity conditions and existence theorems in nonlinear elasticity , 1976 .

[6]  C. Broit.  Optimal registration of deformed images , 1981 .

[7]  A. Raoult.  Non-polyconvexity of the stored energy function of a Saint Venant-Kirchhoff material , 1986 .

[8]  R. Glowinski,et al.  Augmented Lagrangian and Operator-Splitting Methods in Nonlinear Mechanics , 1987 .

[9]  D. Mumford,et al.  Optimal approximations by piecewise smooth functions and associated variational problems , 1989 .

[10]  B. Dacorogna.  Direct methods in the calculus of variations , 1989 .

[11]  P. V. N. Marrero.  A numerical method for detecting singular minimizers of multidimensional problems in nonlinear elasticity , 1990 .

[12]  Michael I. Miller,et al.  Mapping of hyperelastic deformable templates using the finite element method , 1995, Optics & Photonics.

[13]  B. Dacorogna,et al.  Existence of minimizers for non-quasiconvex integrals , 1995 .

[14]  Michael I. Miller,et al.  Deformable templates using large deformation kinematics , 1996, IEEE Trans. Image Process..

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

[16]  Stephen J. Wright,et al.  Numerical Optimization , 2018, Fundamental Statistical Inference.

[17]  B. Vemuri,et al.  A level-set based approach to image registration , 2000, Proceedings IEEE Workshop on Mathematical Methods in Biomedical Image Analysis. MMBIA-2000 (Cat. No.PR00737).

[18]  A. Yezzi,et al.  A variational framework for joint segmentation and registration , 2001, Proceedings IEEE Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA 2001).

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

[20]  Yunmei Chen,et al.  On the incorporation of shape priors into geometric active contours , 2001, Proceedings IEEE Workshop on Variational and Level Set Methods in Computer Vision.

[21]  L. Vese,et al.  A new framework of quantifying differences between images by matching gradient fields and its application to image blending , 2002, 2002 IEEE Nuclear Science Symposium Conference Record.

[22]  S. Osher,et al.  From Landmark Matching to Shape and Open Curve Matching : A Level Set Approach , 2002 .

[23]  L. Younes,et al.  On the metrics and euler-lagrange equations of computational anatomy. , 2002, Annual review of biomedical engineering.

[24]  S. Thiruvenkadam,et al.  FMR image registration using the Mumford-Shah functional and Shape information , 2002 .

[25]  Y. Chen,et al.  Image registration via level-set motion: Applications to atlas-based segmentation , 2003, Medical Image Anal..

[26]  Yunmei Chen,et al.  Joint Image Registration and Segmentation , 2003 .

[27]  Xiao Han,et al.  A Topology Preserving Level Set Method for Geometric Deformable Models , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[28]  Martin Rumpf,et al.  A Variational Approach to Nonrigid Morphological Image Registration , 2004, SIAM J. Appl. Math..

[29]  Paul M. Thompson,et al.  Linear and non-linear geometric object matching with implicit representation , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

[30]  Daniel Rueckert,et al.  Simultaneous Segmentation and Registration for Medical Image , 2004, MICCAI.

[31]  Tony F. Chan,et al.  A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model , 2002, International Journal of Computer Vision.

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

[33]  J. Modersitzki,et al.  A unified approach to fast image registration and a new curvature based registration technique , 2004 .

[34]  E. Haber,et al.  Numerical methods for volume preserving image registration , 2004 .

[35]  Jan Modersitzki,et al.  Curvature Based Image Registration , 2004, Journal of Mathematical Imaging and Vision.

[36]  Alain Trouvé,et al.  Computing Large Deformation Metric Mappings via Geodesic Flows of Diffeomorphisms , 2005, International Journal of Computer Vision.

[37]  F. Santosa,et al.  A topology-preserving level set method for shape optimization , 2004, math/0405142.

[38]  Gregory G. Slabaugh,et al.  Coupled PDEs for non-rigid registration and segmentation , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[39]  Valerie Duay,et al.  Atlas-based segmentation of medical images locally constrained by level sets , 2005, IEEE International Conference on Image Processing 2005.

[40]  Baba C. Vemuri,et al.  Simultaneous Registration and Segmentation of Anatomical Structures from Brain MRI , 2005, MICCAI.

[41]  Eldad Haber,et al.  Image Registration with Guaranteed Displacement Regularity , 2007, International Journal of Computer Vision.

[42]  Baba C. Vemuri,et al.  Simultaneous Registration and Parcellation of Bilateral Hippocampal Surface Pairs for Local Asymmetry Quantification , 2007, IEEE Transactions on Medical Imaging.

[43]  John Ashburner,et al.  A fast diffeomorphic image registration algorithm , 2007, NeuroImage.

[44]  Y. Rouchdy,et al.  A nonlinear elastic deformable template for soft structure segmentation: application to the heart segmentation in MRI , 2007 .

[45]  Martin Rumpf,et al.  Multiscale Joint Segmentation and Registration of Image Morphology , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[46]  Anthony J. Yezzi,et al.  Global Regularizing Flows With Topology Preservation for Active Contours and Polygons , 2007, IEEE Transactions on Image Processing.

[47]  Paul M. Thompson,et al.  Topology Preserving Log-Unbiased Nonlinear Image Registration: Theory and Implementation , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[48]  Luminita A. Vese,et al.  Self-Repelling Snakes for Topology-Preserving Segmentation Models , 2008, IEEE Transactions on Image Processing.

[49]  Luminita A. Vese,et al.  A Combined Segmentation and Registration Framework with a Nonlinear Elasticity Smoother , 2009, SSVM.

[50]  M. Droske,et al.  Mumford–Shah based registration: a comparison of a level set and a phase field approach , 2009 .

[51]  Daniel Rueckert,et al.  Analysis of serial magnetic resonance images of mouse brains using image registration , 2009, NeuroImage.

[52]  Xue-Cheng Tai,et al.  Augmented Lagrangian Method, Dual Methods and Split Bregman Iteration for ROF Model , 2009, SSVM.

[53]  J. Tilak Ratnanather,et al.  Diffeomorphic Active Contours , 2010, SIAM J. Imaging Sci..

[54]  J. Koko,et al.  An Augmented Lagrangian Method for , 2010 .

[55]  Paul M. Thompson,et al.  A Nonconservative Lagrangian Framework for Statistical Fluid Registration—SAFIRA , 2011, IEEE Transactions on Medical Imaging.

[56]  M. Bandstra,et al.  Measurements of Fukushima fallout by the Berkeley Radiological Air and Water Monitoring project , 2011, 2011 IEEE Nuclear Science Symposium Conference Record.