Statistical Validation of Image Segmentation Quality Based on a Spatial Overlap Index

Academic Radiology

Volumn 11, Issue 2, 2004, Pages 178-189

  Zou, Kelly H ^a   Warfield, Simon K ^a   Bharatha, Aditya ^a   Tempany, Clare M C ^a   Kaus, Michael R ^a   Haker, Steven J ^a   Wells III, William M ^a   Jolesz, Ferenc A ^a   Kikinis, Ron ^a  

^a NONE

Author keywords

Brain segmentation; Dice similarity coefficient; Magnetic resonance imaging (MRI); Prostate peripheral zone segmentation; Spatial overlap

Indexed keywords

ALGORITHM; ANALYSIS OF VARIANCE; ARTICLE; BRACHYTHERAPY; BRAIN TUMOR; DIAGNOSTIC ACCURACY; HUMAN; IMAGE QUALITY; NUCLEAR MAGNETIC RESONANCE IMAGING; POSTOPERATIVE PERIOD; PREOPERATIVE EVALUATION; PRIORITY JOURNAL; PROBABILITY; PROSTATE CANCER; REPRODUCIBILITY; STATISTICAL ANALYSIS; VALIDATION PROCESS;

EID: 0942265691     PISSN: 10766332     EISSN: None     Source Type: Journal    
DOI: 10.1016/S1076-6332(03)00671-8     Document Type: Article

References (33)

1. Bonar DC, Schaper KA, Anderson JR, Rottenberg DA, Strother SC. Graphical analysis of MR feature space for measurement of CSF, gray matter, and white-matter volumes. J Comput Assist Tomogr 1993; 17:461-470.
2. Warfield SK, Westin CF, Guttmann CRG, Albert M, Jolesz FA, Kikinis R. Fractional segmentation of white matter. In: Proceedings of Second International Conference on Medical Imaging Computing and Computer Assisted Interventions, Sept 19-22, 1999, Cambridge, UK. New York: Springer, 62-71.
3. Zou KH, Wells M III, Kaus MR, Kikinis R, Jolesz FA, Warfield SK. Statistical validation of automated probabilistic fractional segmentation against composite latent expert gold standard in MR imaging of brain tumors. In: Proceedings of 5th International Conference on Medical Imaging Computing and Computer Assisted Interventions, Sept 25-28, 2002, Tokyo, Japan. Berlin: Springer-Verlag, 315-322.
4. Grabowski TJ, Frank RJ, Szumski NR, Brown CK, Damasio H. Validation of partial tissue segmentation of single-channel magnetic resonance images of the brain. Neuroimage 2000; 12:640-656.
5. Choi HS, Haynor DR, Kim Y. Partial volume tissue classification of multi-channel magnetic resonance images - a mixed model. IEEE Trans Med Imag 1991; 10:295-407.
6. Kao YH, Sorenson JA, Bahn MM, Winkler SS. Dual-echo MRI segmentation using vector decomposition and probability technique: a two-tissue model. Magn Reson Med 1994; 32:342-357.
7. Cuadra MB, Platel B, Solanas E, Butz T, Thiran JP. Validation of tissue modelization and classification techniques of T1-weighted MR brain image. Medical Image Computing and Computer-Assisted Intervention, 2002, Tokyo Japan. Lecture Notes in Computer Science. Berlin, Heidelberg: Springer-Verlag, 2002; 290-297.
8. Kikinis R, Guttmann CRG, Metcalf D, Wells WM, Ettinger GJ, Weiner HL, Jolesz FA. Quantitative follow-up of patients with multiple sclerosis using MRI: technical aspects. J Magn Reson Imaging 1999; 9:519-530.
9. Guttmann CRG, Kikinis R, Anderson MC, et al. Quantitative follow-up of patients with multiple sclerosis using MRI: reproducibility. J Magn Reson Imaging 1999; 9:509-518.
10. Warfield SK, Zou KH, Kaus MR, Wells WM III. Simultaneous validation of image segmentation and assessment of expert quality. International Symposium on Biomedical Imaging, July 7-10, 2002. IEEE 2002; 1494:1-4.
11. Collins DL, Zijdenbos AP, Kollokian V, Sled JG, Kabani NJ, Holmes CJ, Evans AC. Design and construction of a realistic digital brain phantom. IEEE Trans Med Imaging 1998; 17:463-468.
12. Kwan RK-S, Evans AC, Pike GB. MRI simulation-based evaluation of image-processing and classification methods. IEEE Trans Med Imaging 1999; 18:1085-1097.
13. Dice LR. Measures of the amount of ecologic association between species. Ecology 1945; 26:297-302.
14. Fleiss JL. The measurement of interrater agreement. In: Statistical methods for rates and proportions. 2nd ed. New York, NY: John Wiley & Sons, 1981; 212-236.
15. Zijdenbos AP, Dawant BM, Margolin RA, Palmer AC. Morphometric analysis of white matter lesions in MR images: method and validation. IEEE Trans Med Imaging 1994; 13:716-724.
16. Bharatha A, Hirose M, Hata N, et al. Evaluation of three-dimensional finite element-based deformable registration of pre- and intraoperative prostate imaging. Med Phys 2001; 28:2551-2560.
17. Jaccard P. The distribution of flora in the alpine zone. New Phytologist 1912; 11:37-50.
18. Agresti A. Categorical data analysis. New York, NY: John Wiley & Sons, 1990.
19. Zou KH, Tempany CM, Fielding JR, Silverman SG. Original smooth receiver operating characteristic curve estimation from continuous data: statistical methods for analyzing the predictive value of spiral CT of ureteral stones. Acad Radiol 1998; 5:680-687.
20. O'Malle AJ, Zou KH, Fielding JR, Tempany CM. Bayesian regression methodology for estimating a receiver operating characteristic curve with two radiologic applications: prostate biopsy and spiral CT of ureteral stones. Acad Radiol 2001; 8:713-725.
21. Zou KH, Warfield SK, Fielding JR, et al. Statistical validation baseds on parametric receiver operating characteristic analysis of continuous classification data. Acad Radiol 2003; 10:1359-1368.
22. Zou KH, Wells WM III, Kikinis R, Warfield SK. Three validation metrics for automated probabilistic image segmentation of brain tumors. Stat Med 2003 (in press).
23. Gerig G, Jomier M, Chakos M. Valmet: A new validation tool for assessing and improving 3D object segmentation. In: Proceedings of Fourth International Conference on Medical Imaging Computing and Computer Assisted Interventions, Oct 14-17, 2001, Urecht, The Netherlands. Heidelberg: Springer, 2001; 516-523.
24. Huttenlocher DP, Klauderman GA, Rucklidge WJ. Comparing images using the Hausdorff-distance. IEEE Trans Patt Anal Machine Intel 1993; 15:850-863.
25. Kaus MR, Warfield SK, Nabavi A, Black PM, Jolesz FA, Kikinis R. Automated segmentation of MR images of brain tumors. Radiology 2001; 218:586-591.
26. Gering D, Nabavi A, Kikinis R, et al: An integrated visualization system for surgical planning and guidance using image fusion and interventional imaging. In: Proceedings of 2nd International Conference on Medical Imaging Computing and Computer Assisted Interventions, Cambridge, UK. September 19-22, 1999. Heidelberg: Springer-Verlag, 1999; 809-819.
27. Lin CC, Mudholkar GS. A simple test for normality against asymmetric alternatives. Biometrika 1980; 67:455-461.
28. Warfield SK, Zou KH, Wells M III. Validation of image segmentation and expert quality with an expectation-maximization algorithm. In: Proceedings of 5th International Conference on Medical Imaging Computing and Computer Assisted Interventions, Tokyo, Japan, September 22-25, 2002. Berlin: Springer-Verlag, 2002; 298-306.
29. Dempster AP, Laird NM, Rubin DB. Maximum-likelihood from incomplete data via the EM algorithm. J Royal Stat Soc (Ser B) 1977; 39:34-37.
30. Kittler J, Hatef M, Duin RPW, Matas J. On combining classifiers. IEEE Trans Patt Anal Machine Intel 1998; 20:226-239.
31. Johnson NL, Kotz SI, Balakrishnan N. Beta distributions. In: Continuous univariate distributions. 2nd ed. New York, NY: John Wiley and Sons, 1994; 221-235.
32. Donner A. Sample size requirements for the comparison of two or more coefficients of inter-observer agreement. Stat Med 1998; 17:1157-1168.
33. Swets JA. Indices of Discrimination or Diagnostic Accuracy. In: Signal detection theory and roc analysis in psychology and diagnostics. Mahwah, NJ: Lawrence Erlbaum Associates; 19xx, 59-96.