Balancing the role of priors in multi-observer segmentation evaluation

Journal of Signal Processing Systems

Volumn 55, Issue 1-3, 2009, Pages 185-207

  Zhu, Yaoyao ^a   Huang, Xiaolei ^a   Wang, Wei ^a   Lopresti, Daniel ^a   Long, Rodney ^b   Antani, Sameer ^b   Xue, Zhiyun ^b   Thoma, George ^b  

^a Lehigh University   (United States)

^b NATIONAL INSTITUTES OF HEALTH   (United States)

Author keywords

Bayesian decision; Ground truth; Multi observer; Precision; Segmentation; Sensitivity; Specificity; STAPLE; Validation

Indexed keywords

BAYESIAN DECISION; GROUND TRUTH; MULTI-OBSERVER; PRECISION; SEGMENTATION; SENSITIVITY; SPECIFICITY; STAPLE; VALIDATION;

BAYESIAN NETWORKS; WORLD WIDE WEB;

CONVERGENCE OF NUMERICAL METHODS;

EID: 62349100675     PISSN: 19398018     EISSN: 19398115     Source Type: Journal    
DOI: 10.1007/s11265-008-0215-5     Document Type: Article

References (20)

1. Warfield, S. K., Zou, K. H., & Wells, W. M. (2004). Simultaneous Truth and Performance Level Estimation (STAPLE): An algorithm for the validation of image segmentation. IEEE Transactions on Medical Imaging, July.
2. S. Lotenberg H. Greenspan S. Gordon L. R. Long J. Jeronimo S. K. Antani 2007 Automatic evaluation of uterine cervix segmentations Proceedings of SPIE Medical Imaging 6515 65151J 1-12
3. Zhu, Y., Long, L. R., Antani, S. K., Xue, Z., & Thoma, G. R. (2007). Web-based STAPLE for quality estimation of multiple image segmentations. Poster at 20th NIH Research Festival (IMAG-12), National Institutes of Health, September.
4. Y. J. Zhang 1996 A survey on evaluation methods for image segmentation Pattern Recognition 29 8 1335 1346
5. W. A. Yasnoff J. K. Mui J. W. Bacus 1977 Error measures in scene segmentation Pattern Recognition 9 4 217 231
6. B. Qian Huang Dom 1995 Quantitative methods of evaluating image segmentation Proceedings IEEE International Conference on Image Processing 3 53 56
7. Martin, D. (2002). An empirical approach to grouping and segmentation. PhD dissertation, University of California, Berkeley.
8. J. S. Cardoso Corte L. Corte-Real 2005 Toward a generic evaluation of image segmentation IEEE Transactions on Image Processing 14 11 1773 1782
9. Monteiro, F. C., Fernando, C., Campilho, A. C., & Aurélio, C. Performance Evaluation of Image Segmentation. ICIAR06 (I: 248-259).
10. J. Kittler M. Hatef R. P. W. Duin J. Matas 1998 On combining classifiers IEEE Transactions on Pattern Analysis and Machine Intelligence 20 226 239 Mar
11. D. Windridge J. Kittler 2003 A morphologically optimal strategy for classifier combination: Multiple expert fusion as a tomographic process IEEE Transactions on Pattern Analysis and Machine Intelligence 25 343 353 Mar
12. R. A. Jacobs M. I. Jordan S. J. Nowlan G. E. Hinton 1991 Adaptive mixtures of local experts Neural Computation 3 79 87
13. Jordan, M. I., & Jacobs, R. A. Hierarchical Mixtures of Experts and the EM Algorithm. Tech. Rep. AIM-1440, 1993.
14. C. Restif 2007 Revisiting the evaluation of segmentation results: Introducing confidence maps Medical Image Computing and Computer-Assisted Intervention 2 588 595
15. A. Martina H. Laanaya A. Arnold-Bos 2006 Evaluation for uncertain image classification and segmentation Pattern Recognition 39 11 1987 1995 November
16. Berger, J. (1985). Statistical decision theory and bayesian analysis. New York: Springer-Verlag.
17. M. Prasad A. Sowmya I. Koch 2004 Feature subset selection using ICA for classifying emphysema in HRCT images 17th International Conference on Pattern Recognition (ICPR) 4 515 518
18. Prasad, M., Sowmya, A., & Wilson, P. Multi-level classification of emphysema in HRCT lung images. Pattern Analysis & Applications
19. R. Herrero M. H. Schiffman C. Bratti 1997 Design and methods of a population-based natural history study of cervical neoplasia in a rural province of Costa-Rica: The Guanacaste Project Revista Panamericana de Salud Pública 1 5 362 375
20. Huang, X., Wang, W., Xue, Z., Antani, S., Long, L. R., & Jeronimo, J. (2008). Tissue classification using cluster features for lesion detection in digital cervigrams. San Diego: SPIE Medical Imaging.