Image registration with sliding motion constraints for 4D CT motion correction

Informatik aktuell

Volumn , Issue , 2015, Pages 335-340

  Derksen, Alexander ^a   Heldmann, Stefan ^a   Polzin, Thomas ^b   Berkels, Benjamin ^c  

^a FRAUNHOFER MEVIS   (Germany)

^b UNIVERSITY OF LÜBECK   (Germany)

^c RWTH AACHEN UNIVERSITY   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTERIZED TOMOGRAPHY; DEFORMATION; IMAGE PROCESSING; MEDICAL IMAGING; MOTION ANALYSIS;

CONTINUOUS DEFORMATIONS; DEFORMATION FIELD; FINITE-ELEMENT DISCRETIZATION; MOTION CORRECTION; NONLINEAR REGISTRATION; SLIDING MOTIONS; UNSTRUCTURED TETRAHEDRAL MESHES;

IMAGE REGISTRATION;

EID: 85012190997     PISSN: 1431472X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/978-3-662-46224-9_58     Document Type: Conference Paper

References (10)

1. Murphy K, van Ginneken B, Reinhardt JM, et al. Evaluation of registration methods on thoracic CT: the EMPIRE10 challenge. IEEE Trans Med Imaging. 2011;30:1901-20.
2. Galbán CJ, Han MK, Boes JL, et al. Computed tomography-based biomarker provides unique signature for diagnosis of COPD phenotypes and disease progression. Nat Med. 2012;18:1711-5.
3. Rühaak J, Heldmann S, Kipshagen T, et al. Highly accurate fast lung CT registration. Proc SPIE. 2013;8669:86690Y-1-9.
4. Werner R, Ehrhardt J, Schmidt R, et al. Patient-specific finite element modeling of respiratory lung motion using 4D CT image data. Med Phys. 2009;36:1500-11.
5. Schmidt-Richberg A, Werner R, Handels H, et al. Estimation of slipping organ motion by registration with direction-dependent regularization. Med Image Anal. 2012;16:150-9.
6. Pace D, Aylward S, Niethammer M. A locally adaptive regularization based on anisotropic diffusion for deformable image registration of sliding organs. IEEE Trans Med Imaging. 2013;32:2114-26.
7. Han L, Hawkes D, Barratt D. A hybrid biomechanical model-based image registration method for sliding objects. Proc SPIE. 2014;9034:90340G-1-6.
8. Modersitzki J. FAIR: Flexible Algorithms for Image Registration. SIAM; 2009.
9. Castillo R, Castillo E, Guerra R, et al. A framework for evaluation of deformable image registration spatial accuracy using large landmark point sets. Phys Med Biol. 2009;54:1849-70.
10. Lassen B, Kuhnigk JM, Schmidt M, et al. Lung and lung lobe segmentation methods at fraunhofer MEVIS. Proc Int Workshop Pulmon Image Anal. 2011; p. 185-99.