Automatic shape based deformable registration of multiphase contrast enhanced liver CT volumes

Progress in Biomedical Optics and Imaging - Proceedings of SPIE

Volumn 7962, Issue , 2011, Pages

  Erdt, Marius ^a   Sakas, Georgios ^b   Hammon, Matthias ^c   De Beni, Stefano ^d   Solbiati, Luigi ^e   Cavallaro, Alexander ^c  

^a FRAUNHOFER IGD   (Germany)

^b DARMSTADT UNIVERSITY OF TECHNOLOGY   (Germany)

^c UNIVERSITY HOSPITAL ERLANGEN   (Germany)

^d Esaote   (Italy)

^e BUSTO ARSIZIO HOSPITAL   (Italy)

Author keywords

Computed tomography; elastic registration; liver; multi phase CT

Indexed keywords

AUTOMATIC REGISTRATION; CLINICAL PRACTICES; COMPUTED TOMOGRAPHY; CONTRAST-ENHANCED; CONTRAST-ENHANCED CT; CT VOLUME; DEFORMABLE REGISTRATION; DISTANCE-BASED; ELASTIC REGISTRATION; ERROR PRONES; HEPATIC DISEASE; HIGH QUALITY; INTERNAL STRUCTURE; LIVER CT; MULTI-PHASE CT; MULTISTAGE APPROACH; OPERATION PLANNING; PRE-SEGMENTATION; SHAPE BASED; SHAPE INFORMATION; SPEED FUNCTION;

CONTENT BASED RETRIEVAL; DEFORMATION; DIAGNOSIS; IMAGE MATCHING; IMAGE PROCESSING; IMAGING SYSTEMS; MEDICAL IMAGING; RADIOLOGY; TOMOGRAPHY;

COMPUTERIZED TOMOGRAPHY;

EID: 79957978521     PISSN: 16057422     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.878094     Document Type: Conference Paper

References (8)

1. Kwon, D., Yun, I., Lee, K., and Lee, S., "Efficient feature-based nonrigid registration of multiphase liver ct volumes," in [BMVC08], (2008).
2. Huang, X., Wang, B., Cheng, M., Huang, S., and Ju, Y., "Image registration and data fusion for different phases of contrast enhanced liver ct data," in [Bioinformatics and Biomedical Engineering, 2008. ICBBE 2008. The 2nd International Conference on], 2682-2685 (2008).
3. Heldmann, S. and Zidowitz, S., "Elastic registration of multiphase ct images of liver," in [Medical Imaging 2009: Image Processing], Pluim, J. P. W. and Dawant, B. M., eds., 7259(1), 72591H, SPIE (2009).
4. Cootes, T. F., Taylor, C. J., Cooper, D. H., and Graham, J., "Active shape models - their training and application," Computer Vision and Image Understanding 61(1), 38-59 (1995).
5. Heimann, T., Meinzer, H., and Wolf, I., "A statistical deformable model for the segmentation of liver ct volumes," in [MICCAI 2007 Workshop Proceedings: 3D Segmentation in the Clinic: A Grand Challenge], 161-166 (2007).
6. Erdt, M., Kirschner, M., Steger, S., and Wesarg, S., "Fast automatic liver segmentation combining learned shape priors with observed shape deviation," in [IEEE International Symposium on Computer-Based Medical Systems (CBMS)], 249-254 (2010).
7. Erdt, M., Schlegel, P., and Wesarg, S., "Multi-layer deformable models for medical image segmentation," in [10th International Conference on Information Technology and Applications in Biomedicine], 1-4 (2010).
8. Thirion, J. P., "Image matching as a diffusion process: an analogy with maxwell's demons," Medical Image Analysis 2(3), 243-260 (1998).