Automatic segmentation of brain infarction in diffusion weighted MR images

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 5032 III, Issue , 2003, Pages 1531-1542

  Li, Wu ^a   Tian, Jie ^a  

^a INSTITUTE OF AUTOMATION   (China)

Author keywords

Digital brain atlas; DWI; Image segmentation; Infarction; MRI; Statistical classification

Indexed keywords

BRAIN; MAGNETIC RESONANCE IMAGING; MEDICAL IMAGING;

DIFFUSION WEIGHTED IMAGING (DWI);

IMAGE SEGMENTATION;

EID: 0042922583     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.481350     Document Type: Conference Paper

References (27)

1. R. G. Gonzalez, P. W. Schaefer, F. S. Buonanno, L. H. Schwamm, R. F.Budzik, G. Rordorf, B. Wang, A. G.Sorensen, and W. J. Koroshetz, "Diffusion-weighted MR imaging: diagnostic accuracy in patients imaged within 6 hours of stroke symptom onset," Radiology, vol. 210, pp. 155-62, 1999.
2. K. O. Lovblad, H. J. Laubach, A. E. Baird, F. Curtin, G. Schlaug, R. R.Edelman, and S. Warach, "Clinical experience with diffusion-weighted MR in patients with acute stroke [see comments]," AJNR Am J Neuroradiol, vol.19, pp.1061-6, 1998.
3. K. O. Lovblad, A. E. Baird, G. Schlaug, A. Benfield, B. Siewert, B. Voetsch, A. Connor, C. Burzynski, R. R. delman, and S. Warach, "Ischemic lesion volumes in acute stroke by diffusion-weighted magnetic resonance imaging correlate with clinical outcome," Ann Neurol, vol.42, pp. 164-70, 1997.
4. A. E. Baird, A. Benfield, G. Schlaug, B. Siewert, K. O. Lovblad, R. R.Edelman, and S. Warach, "Enlargement of human cerebral ischemic lesion volumes measured by diffusion-weighted magnetic resonance imaging [see comments]," Ann Neurol, vol.41, pp.581-9, 1997.
5. P. A. Barber, D. G. Darby, P. M. Desmond, Q. Yang, R. P. Gerraty, D. Jolley, G. A. Donnan, B. M. Tress, and S. M. Davis, "Prediction of stroke outcome with echoplanar perfusion- and diffusion- weighted MRI," Neurology, vol.51, pp. 418-26, 1998.
6. A.L.Martel, S.J.Allder, G.S.Delay, P.S.Morgan, and A.R. Moody, "Measurement of Infarct Volume in Stroke Patients Using Adaptive Segmentation of Diffusion Weighted MR Images," MICCAI'99, vol.1679, pp.22-31, Cambridge, UK, 1999.
7. K.V.Leemput, F.Maes, D.Vandermeulen, and P.Suetens, "Automated model-based tissue classification of MR images of the brain," IEEE Trans. Med. Imag., vol. 18, no. 10, pp. 897-908, 1999.
8. K.V.Leemput, F.Maes, D.Vandermeulen, and P.Suetens, "Automated model-based bias field correction of MR images of the brain," IEEE Trans. Med. Imag., vol. 18, no. 10, pp. 885-896, 1999.
9. K.V.Leemput, F.Maes, D.Vandermeulen, A.Colchester, and P.Suetens. "Automated segmentation of multiple sclerosis lesions by model outlier detection," IEEE Trans. Med. Imag., vol. 20, no. 8, pp. 677-688, 2001.
10. N. Moon, E. Bullitt, K.V.Leemput, and G.Gerig, "Automatic Brain and Tumor Segmentation," MICCAI2002, T. Dohi and R. Kikinis (Eds.), vol. 2488, pp. 372-379, Tokyo, Japan, 2002.
11. S. K.Warfield, J. Dengler, J. Zaers, C. R. Guttmann, W. M. Wells, G. J. Ettinger, J. Hiller, and R. Kikinis, "Automatic identification of gray matter structures from MRI to improve the segmentation of white matter lesions," Journal of Image Guided Surgery, vol. 1, no. 6, pp. 326-338, 1995.
12. S. K.Warfield, M. Kaus, F. A. Jolesz, and R. Kikinis, "Adaptive, Template Moderated, Spatially Varying Statistical Classification," Medical Image Analysis, vol. 4, no. 1, pp. 43-55, 2000.
13. K.Rohr, H.S.Stiehl, R. Sprengel, T.M.Buzug, J.Weese, and M.H.Kuhn, "Point-based elastic registration of medical image data using approximating thin-plate splines," In Proc. 4th International Conf. Visualization in Biomedical Computing (VBC'96), pp.297-307, Hamburg, Germany, 1996.
14. G.E.Christensen, R.D.Rabbitt, and M.I.Miller, "3D brain mapping using a deformable neuroanatomy," Phys.Med.Biol., vol. 39, pp. 609-618, 1994.
15. S. K. Warfield, A. Robatino, J. Dengler, F. A. Jolesz, and R. Kikinis, "Nonlinear Registration and Template Driven Segmentation," in Brain Warping (A. W. Toga, ed.), ch. 4, pp. 67-84, Academic Press, San Diego, USA, 1999.
16. J.Thirion, "Image matching as a diffusion process: an analogy with maxwell's demons," Medical Image Analysis. vol. 2, no. 3, pp. 243-260, 1998.
17. J. A. Schnabel and S. R. Arridge, "Multi-scale shape description of MR brain images using active contour models", In Proc. SPIE Medical Imaging 1996, vol. 2710, pp. 596-606, Newport Beach, CA, 1996.
18. O.D.Escoda, A.Petrovic and P.Vandergheynst, "Segmentation of Natural Images Using Scale-Space Representations: A Linear and a Non-Linear Approach," In Proc. of EUSIPCO, Toulouse, France, September 2002.
19. J.L.Marroquin, B.C.Vemuri, S.Botello, F.Calderon, and A. Fernandez-Bouzas, "An accurate and efficient Bayesian method for automatic segmentation of brain MRI," IEEE Trans. Med. Imag., vol.21, no.8, pp. 934-945, 2002.
20. P.Perona and J.Malik, "Scale-space and edge detections using anisotropic diffusion," IEEE Trans. Pattern Anal. Machine Intell., vol.12, no.7, pp. 629-639, 1990.
21. J.Canny, "A computational approach to edge detection," IEEE Trans. Pattern Anal. Machine Intell., vol.8, pp.679-698, 1986.
22. J.C.Rajapakse, J.N. Giedd, and J.L.Rapoport, "Statistical Approach to Segmentation of Single-Channel Cerebral MR Images," IEEE Trans. Med. Imag., vol.16, no.2, pp. 176-186, 1997.
23. S.German and D.Geman, "Stochastic relaxation, Gibbs distribution, and the Bayesian restoration of images," IEEE Trans. Pattern Anal. Machine Intell., vol. PAMI-6, pp. 721-741, 1984.
24. A.P.Zijdenbos, B.M.Dawant, R.A.Margolin, and A.C.Palmer, "Morphometric analysis of white matter lesions in MR images: Method and validation," IEEE Trans. Med. Imag., vol. 13, p.4, pp. 716-724, Dec. 1994.
25. M.S.Atkins and B.Mackiewich, "Fully automatic segmentation of the brain in MRI," IEEE Trans. Med. Imag., vol.17, no.1, pp. 98-107, 1998.
26. T.N.Pappas, "An adaptive clustering algorithm for image segmentation," IEEE Trans. Signal Processing, vol. 40, no. 4, pp. 901-914, 1992.
27. J.C.Rajapakse and F.Kruggel, "Segmentation of MR images with intensity inhomogeneities," Image and Vision Computing, UK, Vol. 16, No. 3, pp. 165-180, 1998.