Registration Assisted Image Smoothing and Segmentation

Image segmentation is a fundamental problem in Image Processing, Computer Vision and Medical Imaging with numerous applications. In this paper, we address the atlas-based image segmentation problem which involves registration of the atlas to the subject or target image in order to achieve the segmentation of the target image. Thus, the target image is segmented with the assistance of a registration process. We present a novel variational formulation of this registration assisted image segmentation problem which leads to solving a coupled set of nonlinear PDEs that are solved using efficient numerical schemes. Our work is a departure from earlier methods in that we have a unified variational principle wherein registration and segmentation are simultaneously achieved. We present several 2D examples on syntheticand real data sets along with quantitative accuracy estimates of the registration.

[1]  Michael Unser,et al.  Optimization of mutual information for multiresolution image registration , 2000, IEEE Trans. Image Process..

[2]  Charles R. Meyer,et al.  Demonstration of accuracy and clinical versatility of mutual information for automatic multimodality image fusion using affine and thin-plate spline warped geometric deformations , 1997, Medical Image Anal..

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

[4]  Benoit M. Dawant,et al.  Automatic 3-D segmentation of internal structures of the head in MR images using a combination of similarity and free-form transformations. I. Methodology and validation on normal subjects , 1999, IEEE Transactions on Medical Imaging.

[5]  Jean-Philippe Thirion,et al.  Image matching as a diffusion process: an analogy with Maxwell's demons , 1998, Medical Image Anal..

[6]  Yousef Saad,et al.  Iterative methods for sparse linear systems , 2003 .

[7]  Takeo Kanade,et al.  Quantitative study of brain anatomy , 1998, Proceedings. Workshop on Biomedical Image Analysis (Cat. No.98EX162).

[8]  Martin Styner,et al.  Shape versus Size: Improved Understanding of the Morphology of Brain Structures , 2001, MICCAI.

[9]  Alejandro F. Frangi,et al.  Automatic Construction of 3D Statistical Deformation Models Using Non-rigid Registration , 2001, MICCAI.

[10]  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).

[11]  Philip E. Gill,et al.  Practical optimization , 1981 .

[12]  Rachid Deriche,et al.  Corrections to 'Geodesic Active Contours and Level Sets for the Detection and Tracking of Moving Objects' , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[13]  Michael I. Miller,et al.  Gaussian Random Fields on Sub-Manifolds for Characterizing Brain Surfaces , 1997, IPMI.

[14]  Richard Szeliski,et al.  Hierarchical spline-based image registration , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[15]  J. Shewchuk.  An Introduction to the Conjugate Gradient Method Without the Agonizing Pain , 1994 .

[16]  Daniel Rueckert,et al.  Nonrigid registration using free-form deformations: application to breast MR images , 1999, IEEE Transactions on Medical Imaging.

[17]  Michael I. Miller,et al.  Individualizing Neuroanatomic Atlases Using a Massively Parallel Computer , 1996, Computer.

[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]  Lawrence H. Staib,et al.  Elastic Model Based Non-rigid Registration Incorporation Statistical Shape Information , 1998, MICCAI.

[20]  Alain Trouvé,et al.  Diffeomorphisms Groups and Pattern Matching in Image Analysis , 1998, International Journal of Computer Vision.

[21]  Anthony J. Yezzi,et al.  Curve evolution implementation of the Mumford-Shah functional for image segmentation, denoising, interpolation, and magnification , 2001, IEEE Trans. Image Process..

[22]  Karl Zilles,et al.  A New Approach to Fast Elastic Alignment with Applications to Human Brain , 1996, VBC.

[23]  E ChristensenGary,et al.  Individualizing Neuroanatomical Atlases Using a Massively Parallel Computer , 1996 .

[24]  A Collignon,et al.  Automated multimodality image registration using information theory , 1995 .