Physics-based elastic image registration using splines and including landmark localization uncertainties

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4191 LNCS - II, Issue , 2006, Pages 678-685

  Wörz, Stefan ^a   Rohr, Karl ^a  

^a UNIVERSITY OF HEIDELBERG   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTERIZED TOMOGRAPHY; ELECTROPHORESIS; IMAGE ANALYSIS; MAGNETIC RESONANCE IMAGING; NAVIER STOKES EQUATIONS; SPLINES;

ANISOTROPIC ERRORS; ELASTIC DEFORMATIONS; ELASTIC IMAGE REGISTRATION; GAUSSIAN ELASTIC BODY SPLINES (GEBS); GEL ELECTROPHORESIS IMAGES; PHYSICAL DEFORMATION MODELS;

MEDICAL IMAGING;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; BIOPHYSICS; BRAIN; COMPUTER ASSISTED DIAGNOSIS; ELASTICITY; EVALUATION; HISTOLOGY; HUMAN; IMAGE ENHANCEMENT; IMAGE QUALITY; IMAGE SUBTRACTION; INSTRUMENTATION; MATHEMATICAL COMPUTING; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL MODEL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BIOPHYSICS; BRAIN; ELASTICITY; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MODELS, BIOLOGICAL; MODELS, STATISTICAL; NUMERICAL ANALYSIS, COMPUTER-ASSISTED; PATTERN RECOGNITION, AUTOMATED; PHANTOMS, IMAGING; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SUBTRACTION TECHNIQUE;

EID: 84883831870     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11866763_83     Document Type: Conference Paper

References (11)

1. Zitova, B., Flusser, J.: Image Registration Methods: a Survey. Image and Vision Computing 24 (2003) 977-1000
2. Davis, M., Khotanzad, A., Flaming, D., Harms, S.: Physics-based coordinate transformation for 3D image matching. IEEE Trans. Med. Imag. 16 (1997) 317-328
3. Joshi, S., Miller, M.: Landmark Matching Via Large Deformation Diffeomorphisms. IEEE Trans. on Image Processing 9 (2000) 1357-1370
4. Rohr, K., Stiehl, H., Sprengel, R., Buzug, T., Weese, J., Kuhn, M.: Landmark-Based Elastic Registration Using Approximating Thin-Plate Splines. IEEE Trans. on Medical Imaging 20 (2001) 526-534
5. Kohlrausch, J., Rohr, K., Stiehl, H.: A New Class of Elastic Body Splines for Nonrigid Registration of Medical Images. In: Proc. BVM, Springer (2001) 164-168
6. Johnson, H., Christensen, G.: Consistent Landmark and Intensity-based Image Registration. IEEE Trans. on Medical Imaging 21 (2002) 450-461
7. Rohde, G., Aldroubi, A., Dawant, B.: The adaptive bases algorithm for intensity based nonrigid image registration. IEEE Trans. Med. Imag. 22 (2003) 1470-79
8. Park, H., Bland, P., Brock, K., Meyer, C.: Adaptive registration using local information measures. Medical Image Analysis 8 (2004) 465-473
9. Kohlrausch, J., Rohr, K., Stiehl, H.: A New Class of Elastic Body Splines for Non-rigid Registration of Medical Images. J. Math. Imag. Vis. 23 (2005) 253-280
10. Pekar, V., Gladilin, E., Rohr, K.: An adaptive irregular grid approach for 3-D deformable image registration. Physics in Med. and Biol. 51 (2006) 361-377
11. Kerdok, A., Cotin, S., Ottensmeyer, M., Galea, A., Howe, R., Dawson, S.: Truth cube: Establishing physical standards for soft tissue simulation. Medical Image Analysis 7 (2003) 283-291