Efficient abdominal segmentation on clinically acquired CT with SIMPLE context learning

Progress in Biomedical Optics and Imaging - Proceedings of SPIE

Volumn 9413, Issue , 2015, Pages

  Xu, Zhoubing ^a   Burke, Ryan P ^a   Lee, Christopher P ^a   Baucom, Rebeccah B ^b   Poulose, Benjamin K ^b   Abramson, Richard G ^b   Landman, Bennett A ^a,b  

^a VANDERBILT UNIVERSITY   (United States)

^b VANDERBILT UNIVERSITY   (United States)

Author keywords

Context Learning; Kidneys; Liver; Multi Atlas Segmentation; SIMPLE; Spleen

Indexed keywords

CLASSIFICATION (OF INFORMATION); DATA MINING; DIAGNOSIS; GRAPHIC METHODS; IMAGE PROCESSING; IMAGE SEGMENTATION; ITERATIVE METHODS; LIVER; MEDICAL IMAGE PROCESSING; MEDICAL IMAGING;

COMBINED SEGMENTATIONS; CONTEXT LEARNING; GRAPH-CUT TECHNIQUES; KIDNEYS; PROSTATE RADIOTHERAPY; SIMPLE; SPLEEN; STATE-OF-THE-ART APPROACH;

COMPUTERIZED TOMOGRAPHY;

EID: 84930949615     PISSN: 16057422     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.2081012     Document Type: Conference Paper

References (14)

1. M. G. Linguraru, J. A. Pura, V. Pamulapati et al., "Statistical 4D graphs for multi-organ abdominal segmentation from multiphase CT, " Medical image analysis, 16(4), 904-914 (2012).
2. A. Shimizu, R. Ohno, T. Ikegami et al., "Segmentation of multiple organs in non-contrast 3D abdominal CT images, " International journal of computer assisted radiology and surgery, 2(3-4), 135-142 (2007).
3. M. R. Sabuncu, B. T. Yeo, K. Van Leemput et al., "A generative model for image segmentation based on label fusion, " IEEE transactions on medical imaging, 29(10), 1714-29 (2010).
4. R. Wolz, C. Chu, K. Misawa et al., "Automated abdominal multi-organ segmentation with subject-specific atlas generation, " IEEE transactions on medical imaging, 32(9), 1723-30 (2013).
5. T. R. Langerak, U. A. van der Heide, A. N. Kotte et al., "Label fusion in atlas-based segmentation using a selective and iterative method for performance level estimation (SIMPLE), " Medical Imaging, IEEE Transactions on, 29(12), 2000-2008 (2010).
6. L. R. Dice, "Measures of the amount of ecologic association between species, " Ecology, 26(3), 297-302 (1945).
7. Z. Xu, A. J. Asman, P. L. Shanahan et al., "SIMPLE IS a Good Idea (and Better with Context Learning), " Proceedings of Medical Image Computing and Computer Assisted Intervention (MICCAI), in press, (2014).
8. H. Wang, J. W. Suh, S. R. Das et al., "Multi-Atlas Segmentation with Joint Label Fusion, " IEEE transactions on pattern analysis and machine intelligence, (2012).
9. Y. Boykov, O. Veksler, and R. Zabih, "Fast approximate energy minimization via graph cuts, " Pattern Analysis and Machine Intelligence, IEEE Transactions on, 23(11), 1222-1239 (2001).
10. S. K. Warfield, K. H. Zou, and W. M. Wells, "Simultaneous truth and performance level estimation (STAPLE): an algorithm for the validation of image segmentation, " IEEE Trans Med Imaging, 23(7), 903-21 (2004).
11. A. J. Asman, and B. A. Landman, "Robust statistical label fusion through COnsensus Level, Labeler Accuracy, and Truth Estimation (COLLATE), " IEEE Trans Med Imaging, 30(10), 1779-94 (2011).
12. K. Van Leemput, F. Maes, D. Vandermeulen et al., "Automated model-based bias field correction of MR images of the brain, " IEEE transactions on medical imaging, 18(10), 885-896 (1999).
13. M. J. McAuliffe, F. M. Lalonde, D. McGarry et al., "Medical image processing, analysis and visualization in clinical research, " Computer-Based Medical Systems, 2001. CBMS 2001. Proceedings. 14th IEEE Symposium on, 381-386 (2001).
14. D. Rueckert, L. I. Sonoda, C. Hayes et al., "Nonrigid registration using free-form deformations: Application to breast MR images, " IEEE transactions on medical imaging, 18(8), 712-721 (1999).