Foibles, follies, and fusion: Assessment of statistical label fusion techniques for web-based collaborations using minimal training

Progress in Biomedical Optics and Imaging - Proceedings of SPIE

Volumn 7962, Issue , 2011, Pages

  Asman, Andrew J ^a   Scoggins, Andrew G ^a   Prince, Jerry L ^b   Landman, Bennett A ^a,c  

^a VANDERBILT UNIVERSITY   (United States)

^b Johns Hopkins University   (United States)

^c Johns Hopkins University   (United States)

Author keywords

delineation; label fusion; labeling; minimal training; Parcellation; STAPLE; STAPLER

Indexed keywords

DELINEATION; MINIMAL TRAINING; PARCELLATION; STAPLE; STAPLER;

ESTIMATION; IMAGE PROCESSING; IMAGING SYSTEMS; MAGNETIC RESONANCE IMAGING; MEDICAL IMAGING; RESONANCE; USER INTERFACES;

STATISTICS;

EID: 79958002613     PISSN: 16057422     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.877471     Document Type: Conference Paper

References (12)

1. B. Landman, H. Wan, J. Bogovic, and J. Prince, "Simultaneous Truth and Performance Level Estimation with Incomplete, Over-complete, and Ancillary Data," SPIE Medical Imaging Conference, San Diego, CA.(2010).
2. M. Kearns, and L. G. Valiant, "Learning boolean formulae or finite automata is as hard as factoring," Harvard University Technical Report, TR-14-88, (1988).
3. R. E. Shapire, "The strength of weak learnability," Machine Learning, 5(2), 197-227 (1990).
4. Y. Freund, and R. E. Schapire, "A decision-theoretic generalization of on-line learning and an application to boosting," J. Computer and System Sciences, 55(119-139), (1997).
5. S. K. Warfield, K. H. Zou, M. R. Kaus, and W. M. Wells, [Simultaneous validation of image segmentation and assessment of expert quality], Washington, DC(2002).
6. 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).
7. T. Rohlfing, D. B. Russakoff, and C. R. Maurer, "Expectation maximization strategies for multi-atlas multi-label segmentation," Inf Process Med Imaging, 18, 210-21 (2003).
8. J. Udupa, V. LeBlanc, Y. Zhuge, C. Imielinska, H. Schmidt, L. Currie, B. Hirsch, and J. Woodburn, "A framework for evaluating image segmentation algorithms," Comp Med Imag Graphics 30(2), 75-87 (2006).
9. J. Bogovic, B. A. Landman, P.-L. Bazin, and J. L. Prince, "Statistical Fusion of Surface Labels provided by Multiple Raters, Over-complete, and Ancillary Data," SPIE Medical Imaging Conference, San Diego, CA.(2010).
10. B. A. Landman, J. Bogovic, and J. L. Price, "Efficient Anatomical Labeling by Statistical Recombination of Partially Label Datasets," International Society for Magnetic Resonance in Medicine, Honolulu, HI.(2009).
11. J. C. Gee, M. Reivich, and R. Bajcsy, "Elastically deforming 3D atlas to match anatomical brain images," J. Comput. Assist. Tomogr., 17, 225-236 (1993).
12. P. Jaccard, "The distribution of flora in the alpine zone," New Phytol. , 11, 37-50 (1912).