A framework for evaluating image segmentation algorithms

Computerized Medical Imaging and Graphics

Volumn 30, Issue 2, 2006, Pages 75-87

  Udupa, Jayaram K ^a   LeBlanc, Vicki R ^b   Zhuge, Ying ^a   Imielinska, Celina ^b,c   Schmidt, Hilary ^b   Currie, Leanne M ^d   Hirsch, Bruce E ^e   Woodburn, James ^f  

^a UNIVERSITY OF PENNSYLVANIA   (United States)

^b Columbia University College of Physicians and Surgeons ^*  (United States)

^c Columbia University ^*  (United States)

^d Och Spine at New York Presbyterian Hospitals   (United States)

^e DREXEL UNIVERSITY COLLEGE OF MEDICINE   (United States)

^f UNIVERSITY OF LEEDS   (United Kingdom)

Author keywords

Evaluation of segmentation; Image analysis; Image segmentation; Segmentation efficacy

Indexed keywords

ALGORITHMS; COMPUTATIONAL METHODS; IMAGE ANALYSIS; OBJECT RECOGNITION; STATISTICAL METHODS;

DELINEATION; EVALUATION OF SEGMENTATION; SEGMENTATION ALGORITHMS; SEGMENTATION EFFICACY;

IMAGE SEGMENTATION;

ALGORITHM; ARTICLE; CONTROLLED STUDY; DIAGNOSTIC ACCURACY; EVALUATION; HUMAN; IMAGE ANALYSIS; INTERMETHOD COMPARISON; MATHEMATICAL ANALYSIS; METHODOLOGY; PRIORITY JOURNAL; RECOGNITION; RELIABILITY; STATISTICAL ANALYSIS; TRAINING; VALIDITY;

ALGORITHMS; BRAIN; CLINICAL MEDICINE; EVALUATION STUDIES; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED;

EID: 33645875612     PISSN: 08956111     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compmedimag.2005.12.001     Document Type: Article

References (29)

1. Pal N.R., and Pal S.K. A review on image segmentation techniques. Pattern Recogn 26 (1993) 1277-1294
2. Pham D., Xu C., and Prince J. Current methods in medical image segmentation. Annu Rev Biomed Eng 2 (2000) 315-337
3. Yasnoff W., Mui J., and Bacus J. Error measures for scene segmentation. Pattern Recogn 9 (1977) 217-231
4. Chalana V., and Kim Y. A methodology for evaluation of boundary detection algorithms on medical images. IEEE Trans Med Imaging 16 (1997) 642-652
5. Hoover A., Jean-Baptiste G., Jiang X., Flynn P., Bunke H., Goldgof D., et al. An experimental comparison of range image segmentation algorithms. IEEE Trans Pattern Anal Mach Intell 18 (1996) 673-689
6. Zhang Y. A survey on evaluation methods for image segmentation. Pattern Recogn 29 (1996) 1335-1346
7. Bowyer K. Validation of medical image analysis techniques. In: Beutel J., Kundel H., and Metter R.v. (Eds). The Handbook of Medical Imaging (2000), SPIE
8. Loughlin M., Carlbom I., Busch C., Douglas T., Egevad L., Frimmel H., et al. Three-dimensional modeling of biopsy protocols for localized prostate cancer. Comput Med Imaging Graph 22 (1998) 229-238
9. McFarland E., Brink J., Pilgram T., Heiken J., Balfe D., Hirselj D., et al. Spiral CT colonography: reader agreement and diagnostic performance with two- and three-dimensional image-display techniques. Radiology 218 (2001) 375-383
10. De Graaf C., Koster A., Vinken K., and Viergever M. A methodology for the validation of image segmentation methods. IEEE Symp Comput Based Med Syst Proc (1992) 17-24
11. Dawant B., Hartmann S., Thirion J., Maes F., Vandereulen D., and Demaerel P. Automatic 3-D segmentation of internal structures of the head in MR images using a combination of similarity and free-form transformation. Part 1, methodology and validation on normal subjects. IEEE Trans Med Imaging 10 (1999) 909-916
12. Brown M., Feng W., Hall T., McNitt-Gray M., and Churchill B. Knowledge-based segmentation of pediatric kidneys in CT for measurement of parenchymal volume. J Comput Assist Tomogr 25 (2001) 639-648
13. Huttenlocher D., Klanderman G., and Rucklidge W. Comparing images using the Hausdorff distance. IEEE Trans Pattern Anal Mach Intell 15 (1993) 850-863
14. Udupa J.K., LeBlanc V.R., Schmidt H., Imielinska C., Saha P.K., Grevera G.J., et al. A methodology for evaluating image segmentation algorithms. SPIE Proc 4684 (2002) 266-277
15. Warfield S.K., Zou K.H., and Wells W.M. Simultaneous truth and performance level estimation (STAPLE): an algorithm for the validation of image segmentation. IEEE Trans Med Imaging 23 7 (2004) 903-921
16. Filippi M., Horsfield M., Bressi S., Martinelli V., Baratti C., and Reganatr P. Intra- and inter-observer variability of brain MRI lesion volume measurements in multiple sclerosis: a comparison of techniques. Brain 118 (1995) 1593-1600
17. Wicks D., Tofts P., Miller D., Du B.G., Feinstein A., and Sacares R. Volume measurement of multiple sclerosis lesions with magnetic resonance images: a preliminary study. Neuroradiology 34 (1992) 475-479
18. Patty D., and Li D. Interferon beta-1b is effective in relapsing-remitting multiple sclerosis, II. MRI analysis results of a multicenter, randomized, double blind, placebo-controlled trial,UBC MS/MRI Study Group and the IFNB Multiple Sclerosis Study Group. Neurology 43 (1993) 662-667
19. Pizer S.M. Intensity mappings to linearize display devices. Comput Graph Image Proc 17 (1981) 262-268
20. Nyúl L.G., and Udupa J.K. On standardizing the MR image intensity scale. Magn Reson Med 42 (1999) 1072-1081
21. Browne JA, Herman GT, Odhner D. SNARK93-a programming systems for image reconstruction from projections. Department of Radiology, University of Pennsylvania, Technical report MIPG198; 1993.
22. Collins D.L., Zijdenbos A.P., Kollokian V., Sled J.G., Kabani N.J., Holmes C.J., et al. Design and construction of a realistic digital brain phantom. IEEE Trans Med Imaging 17 (1998) 463-468
23. Nyúl L.G., and Udupa J.K. A Protocol-independent brain MRI segmentation method. SPIE Proc 4684 (2002) 1588-1599
24. Metz C.E., Goodenough D.J., and Rossmann K. Evaluation of receiver operating characteristic curve data in terms of information theory with applications in radiology. Radiology 108 (1973) 297-303
25. van Ginneken B., Frangi A.F., Staal J.J., ter Haar Romeny B.M., and Viergever M.A. Active shape model segmentation with optimal features. IEEE Trans Med Imaging 21 (2002) 924-933
26. Falcão A.X., Udupa J.K., Samarasekera S., and Sharma S. User-steered image segmentation paradigms: live wire and live lane. Graph Models Image Process 60 (1998) 233-260
27. Udupa J.K., Wei L., Samarasekera S., Miki Y., Buchem M.A., and Grossman R.I. Multiple sclerosis lesion quantification using fuzzy connectedness principles. IEEE Trans Med Imaging 16 (1997) 598-609
28. Stindel E., Udupa J.K., Hirsch B.E., and Odhner D. An in vivo analysis of the peri-talar joint complex based on MR imaging. IEEE Trans Biomed Eng 48 (2001) 236-247
29. Rencher AC. Multivariate analysis of variance. In: Methods of multivariate analysis. New York, NY: Wiley; 1995. p. 174-257.