Phantom-based performance evaluation: Application to brain segmentation from magnetic resonance images

Medical Image Analysis

Volumn 4, Issue 4, 2000, Pages 303-316

  Moretti, Bruno ^a,b   Fadili, Jalal Mohamed ^a,b   Ruan, Su ^a   Bloyet, Daniel ^a   Mazoyer, Bernard ^b,c  

^a Centre National de la Recherche Scientifique   (France)

^b GIP CYCERON   (France)

^c CHU CÔTE DE NACRE   (France)

Author keywords

Brain segmentation; Magnetic resonance image; Performance quantification; Validation

Indexed keywords

ALGORITHM; ARTICLE; BRAIN; HISTOLOGY; HUMAN; IMAGE PROCESSING; IMAGE QUALITY; NUCLEAR MAGNETIC RESONANCE IMAGING; PROBABILITY;

ALGORITHMS; BRAIN; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MARKOV CHAINS; PHANTOMS, IMAGING;

EID: 0034567216     PISSN: 13618415     EISSN: None     Source Type: Journal    
DOI: 10.1016/S1361-8415(00)00021-9     Document Type: Article

References (56)

1. Aboutanos, G.B., Dawant, B.M., 1997. Automatic brain segmentation and validation: image-based versus atlas-based deformable models. IEEE Proc. SPIE-Med. Imaging 3034, 299-310.
2. Ashton, E.A., Parker, K.J., Berg, M.J., Chen, C.W., 1997. A novel volumetric feature extraction technique with applications to MR images. IEEE Trans. Med. Imaging 16 (4), 365-371.
3. Barrett, H.H., 1996. Objective evaluation of image quality. In: Second IEEE EMBS International Summer School on Biomedical Imaging. Berder Island, France.
4. Bedekar, A.S., Haralick, R.M., Ramesh, V., Zhang, X., 1994. A bayesian corner detector: theory and performance evaluation. ARPA 94, 703-715.
5. Bloch, F., Hansen, W.W., Packard, M., 1946. The nuclear induction experiment. Phys. Rev. 70, 474-485.
6. Bomans, M., Hohne, K.H., Tiede, U., Riemer, M., 1990. 3-D segmentation of MR images of the head for 3D display. IEEE Trans. Med. Imaging 9, 177-183.
7. Borgefors, G., 1986. Distance transformations in digital images. Comput. Vision Graph. Image Process. 34, 344-371.
8. Broderick, J.F., Narayan, S., Gaskill, M., Dhawan, A.P., Khoury, J., 1996. Volumetric measurement of multifocal brain lesions. Implications for treatment trials of vascular dementia and multiple sclerosis. J. Neuroimaging 6 (1), 36-43.
9. Brummer, M.E., Mersereau, R.M., Eisner, R.L., Lewine, R.R.J., 1993. Automatic detection of brain contour in MRI data sets. IEEE Trans. Med. Imaging 12 (2), 153-166.
10. Chakraborty, A., Staib, L.H., Duncan, J.S., 1996. Deformable boundary finding in medical images by integrating gradient and region information. IEEE Trans. Med. Imaging 15 (6), 859-870.
11. Chalana, V., Kim, Y., 1997. A methodology for evaluation of boundary detection algorithms on medical images. IEEE Trans. Med. Imaging 16 (5), 642-652.
12. Cho, K.J., Meer, P., Cabrera, J., 1997. Performance assessment through bootstrap. IEEE Trans. Pattern Anal. Mach. Intell. 19 (11), 1185-1197.
13. Cline, H.E., Dumoulin, C.L., Hart, Jr. H.R., Lorensen, W., Ludke, S., 1987. 3D reconstruction of the brain from magnetic resonance images using a connectivity algorithm. Magn. Reson. Imaging Magnet 5 (5), 345-352.
14. Collins, D.L., Zijdenbos, A.P., Kollokian, V., Sled, J.G., Kabani, N.J., Holmes, C.J., Evans, A.C., 1998. Design and construction of a realistic digital brain phantom. IEEE Trans. Med. Imaging 17 (3), 463-468.
15. Cootes, T.F., Hill, A., Taylor, C.J., Haslam, J., 1994. The use of active shape models for locating structures in medical images. Image Vision Comput. 12 (6), 355-366.
16. De Munck, J.C., Verster, F.C., Dubois, H.A., Habraken, J.B., Boltjes, B., Claus, J.J., Van Herk, M., 1998. Registration of MR and SPECT without using external fiducial markers. Phys. Med. Biol. 43 (5), 1255-1269.
17. Disler, D.G., Marr, D.S., Rosenthal, D.L., 1994. Accuracy of volume measurements of computed tomography and magnetic resonance imaging phantoms by three-dimensional reconstruction and preliminary clinical application. Invest. Radiol. 29 (8), 739-745.
18. Eggers, H., 1998. Two fast Euclidean distance transformations in Z2 based on sufficient propagation. Comput. Vision Image Understanding 69 (1), 106-116.
19. Frisoni, G.B., Laakso, M.P., Beltramello, A., Geroldi, C., Bianchetti, A., Soininen, H., Trabucehi, M., 1999. Hippocampal and entorhinal cortex atrophy in frontotemporal dementia and Alzheimer's disease. Neurology 52 (1), 91-100.
20. Galloway Jr., R.L., Maciunas, R.J., Edwards II, C.A., 1992. Interactive image-guided neurosurgery. IEEE Trans. Biomed. Eng. 39 (12), 1226-1231.
21. Galloway Jr., R.L., Edwards II, C.A., Lewis, J.T., Maciunas, R.J., 1993. Image display and surgical visualization in interactive image-guided neurosurgery. Opt. Eng. 32, 1955-1962.
22. Ge, Y., Fitzpatrick, J.M., 1996. On the generation of skeletons from discrete Euclidean distance maps. IEEE Trans. Pattern Anal. Mach. Intell. 18 (11), 1055-1066.
23. Gerritsen, F.A., van Veelen, C.W.M., Mali, W.P., Bart, A.I.M., de Bliek, H.L.T., Buurman, J., van Eeuwijk, A.H.W., Hartkamp, M.J., Lobregt, S., Moreira Pereira Ramos, L., Polman, L.J., van Rijen, P.C., Visser, C.P., 1995. Some requirements for and experience with COVIRA algorithms for registration and segmentation. In: Beolchi, L., Kuhn, M.H. (Eds.), Medical Imaging, pp. 4-27.
24. Grimson, W.E.L., Ettinger, G.J., White, S.J., Lozano-Perez, T., Wells, W.M., Kikinis, R., 1996. An automatic registration method for frameless stereotaxy, image guided surgery, and enhanced reality visualization. IEEE Trans. Med. Imaging 15, 129-140.
25. Haralick, R.M., 1994. Dialogue: performance characterization in computer vision. Comput. Vision Graph. Image Process.: Image Understanding 60 (2), 245-265.
26. Heath, M.D., 1996. A robust visual method for assessing the relative performance of edge detection algorithms. Master's Thesis, Tampa, FL.
27. Heath, M.D., Sarkar, S., Sanocki, T., Bowyer, K.W., 1997. A robust visual method for assessing the relative performance of edge-detection algorithms. IEEE Trans. Pattern Anal. Mach. Intell. 19 (12), 1338-1359.
28. Henkelman, M., 1985. Measurement of signal intensities in the presence of noise in MR images. Med. Phys. 12 (2), 232-233.
29. Hoover, A., Gillian, J.-B., Jiang, X., Flynn, P.J., Bunke, H., Goldgof, D.B., Bowyer, K., Eggert, D.W., Fitzgibbon, A., Fisher, R.B., 1996. An experimental comparison of range image segmentation algorithms. IEEE Trans. Pattern Anal. Mach. Intell. 18 (7), 673-689.
30. Huttenlocher, D.P., Klanderman, G.A., Rucklidge, W.J., 1993. Comparing images using the Hausdorff distance. IEEE Trans. Pattern Anal. Mach. Intell. 15 (9), 850-863.
31. Jack, C.R., Marsh, W.R., Hirschom, K.A., Sharbrough, F.W., Cascino, G.D., Karwoski, R.A., Robb, R.A., 1990. EEC scalp electrode projection onto three-dimensional surface rendered images of the brain. Radiology 176 (2), 413-418.
32. Jain, R.C., Binford, T.O., 1991. Ignorance, myopia and naivete in computer vision systems. Comp. Vision Graph. Image Process.: Image Understanding 53 (1), 112-117.
33. Joliot, M., Mazoyer, B., 1993. Three-dimensional segmentation and interpolation of magnetic resonance brain images. IEEE Trans. Med. Imaging 12 (2), 269-277.
34. Juottonen, K., Laakso, M.P., Partanen, K., Soininen, H., 1999. Comparative MR analysis of the entorhinal cortex and hippocampus in diagnosing Alzheimer disease. Am. J. Neuroradiol. 20 (1), 139-144.
35. Kalender, W., 1992. A phantom for standardization and quality control in peripheral bone measurements by QCT and DXA: Design considerations and specifications. Med. Phys. 19, 583-586.
36. Kanungo, T., Jaisimha, M.Y., Palmer, J., Haralick, R.M., 1995. A methodology for quantitative performance evaluation of detection algorithms. IEEE Trans. Image Process. 4 (12), 1667-1674.
37. Kapur, T., Grimson, W.E.L., Wells III, W.M., Kikinis, R., 1996. Segmentation of brain tissue from magnetic resonance images. Med. Image Anal. 1 (2), 109-127.
38. Kass, M., Witkin, A., Terzopoulos, D., 1988. Snakes: active contour models. Int. J. Comput. Vision, 321-331.
39. Kuzniecky, R.I., Burgard, S., Bilir, E., Morawetz, R., Gilliam, F., Faught, E., Black, L., Palmer, C., 1996. Qualitative MRI segmentation in mesial temporal sclerosis: clinical correlations. Epilepsia 37 (5), 433-439.
40. Kwan, R.K.S., Evans, A.C., Pike, G.B., 1996. An extensible MRI simulator for post-processing evaluation. In: Visualization in Biomedical Computing. Fourth International Conference Proceedings. Lecture Notes in Computer Science, Vol. 1131. Springer, pp. 135-140.
41. Malandain, G., Fernandez-Vidal, S., Rocchisani, J.M., 1995. Physically-based rigid registration of 315 free-form objects: application to medical imaging. Research Report INRIA, No. 2453.
42. Mangin, J.F., Frouin, V., Bloch, I., Bendriem, B., Lopez-Krahe, J., 1994. Fast nonsupervised 3D registration of PET and MR images of the brain. J. Cereb. Blood Flow Metab. 14 (5), 749-762.
43. Mortelmans, L., Nuyts, J., Vanhaecke, J., Verbruggen, A., De Roo, M., De Geest, H., Suetens, P., Van de Werf, F., 1993. Experimental validation of a new quantitative method for the analysis of infarct size by cardiac perfusion tomography (SPECT). Int. J. Card. Imaging 9 (3), 201-212.
44. Nastar, C., Ayache, N., 1992. Fast segmentation tracking and analysis of deformable objects. Research Report INRIA, No 1783.
45. Pavlidis, T., Liow, Y.T., 1990. Integrating region growing and edge detection. IEEE Trans. Pattern Anal. Mach. Intell. 12 (3), 225-233.
46. Pelizzari, C., Chen, G., Spelbring, D., Weichselbaum, R., Chen, C., 1989. Accurate three dimensional registration of CT, PET and/or MR images of the brain. J. Comput. Assisted Tomogr. 13, 20-26.
47. Raman, S.V., Sarakar, S., Boyer, K.L., 1991. Tissue boundary refinement in MRI using contour-based scale space matching. IEEE Trans. Med. Imaging 10 (2), 109-121.
48. Ruan, S., Jaggi, C., Bloyet, D., Mazoyer, B. (Eds.), 1998. Brain Tissue Classification in MR Images Based on 3D MRF Model. IEEE EMBS, Hong Kong, p. 625.
49. Suzuki, H., Toriwaki, J., 1991. Automatic segmentation of head MRI images by knowledge guided thresholding. Comput. Med. Imaging Graph. 15 (4), 233-240.
50. Tofts, P.S., Barker, G.J., Filippi, M., Gawne-Cain, M., Lai, M., 1997. An oblique cylinder contrast-adjusted (OCCA) phantom to measure the accuracy of MRI brain lesion volume estimation schemes in multiple sclerosis. Magn. Reson. Imaging 15 (2), 183-192.
51. Turkington, T.G., Hoffman, J.M., Jasezak, R.J., MacFall, J.R., Harris, C.C., Kilts, C.D., Pelizzari, C.A., Coleman, R.E., 1995. Accuracy of surface fit registration for PET and MR brain images using full and incomplete brain surfaces. J. Comput. Assisted Tomogr. 19 (1), 117-124.
52. van Gennip, E.M., Talmon, J.L., 1995. Assessment and Evaluation of Information Technologies in Medicine. IOS Press, Amsterdam.
53. Vannier, M.W., Brundsen, B.S., Hildeholt, C.F., Falk, D., Cheverud, J.M., Figiel, G.S., Perman, W.H., Kohn, L.A., Robb, R.A., Yoffie, R.I., Bresina, S., 1991. Brain surface cortical sulcal lengths: quantification with three-dimensional MR imaging. Radiology 180 (2), 479-484.
54. Vérard, L., Allan, P., Ruan, S., Travère, I.M., Bloyet, D., 1995. 3D brain structures extraction using fully automated MRI segmentation. Information Processing in Medical Imaging, Brest, France, pp. 373-374.
55. Verwer, B.I.H., Verbeek, P.W., Dekker, S.T., 1989. An efficient uniform cost algorithm applied to distance transforms. IEEE Trans. Pattern Anal. Mach. Intell. 11 (4), 424-429.
56. Zhang, Y.J., 1994. Evaluation and comparison of different segmentation algorithms. Patt. Recogn. Lett. 18, 963-974.