T1- and T2-weighted spatially constrained fuzzy C-means clustering for brain MRI segmentation

Progress in Biomedical Optics and Imaging - Proceedings of SPIE

Volumn 7623, Issue PART 1, 2010, Pages

  Despotović, Ivana ^a   Goossens, Bart ^a   Vansteenkiste, Ewout ^a   Philips, Wilfried ^a  

^a GHENT UNIVERSITY   (Belgium)

Author keywords

Fuzzy C Means; Image segmentation; Magnetic resonance imaging; Spatial information

Indexed keywords

ANATOMICAL VARIABILITY; BRAIN DISEASE; BRAIN IMAGES; BRAIN MRI; BRAIN TISSUE; CLINICAL ANALYSIS; COMPLICATED STRUCTURES; COMPUTER ASSISTED DIAGNOSIS; FCM ALGORITHM; FUZZY C MEAN; FUZZY C MEANS CLUSTERING; FUZZY C-MEANS CLUSTERING ALGORITHMS; FUZZY CLUSTERING TECHNIQUES; GESTATIONAL AGE; HIGHLY SENSITIVE; INTENSITY PROFILES; MRI IMAGE; MRI SCAN; NOISE LEVELS; SEGMENTATION RESULTS; SPATIAL INFORMATION; SPATIAL INFORMATIONS; SURGICAL PLANNING; TISSUE SEGMENTATION;

CLUSTERING ALGORITHMS; COMPUTER AIDED ANALYSIS; FUZZY CLUSTERING; FUZZY SYSTEMS; IMAGING SYSTEMS; MAGNETIC RESONANCE IMAGING; MEDICAL IMAGING; PEDIATRICS; RESONANCE; TISSUE;

IMAGE SEGMENTATION;

EID: 79751474305     PISSN: 16057422     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.843892     Document Type: Conference Paper

References (16)

1. Prastawa, M., Gilmore, J. H., Lin, W., and Gerig, G., "Automatic segmentation of MR images of the developing newborn brain," Med. Image Anal. 9, 457-466 (2005).
2. Weisenfeld, N. I. and Warfield, S. K., "Automatic segmentation of newborn brain MRI," Neuroimage 47, 564-572 (2009).
3. Wells, W. M., Grimson, W. E. L., Kikinis, R., and Jolesz, F. A., "Adaptive segmentation of MRI data," IEEE Trans. Med. Imag. 15, 429-442 (1996).
4. Leemput, K. V., Maes, F., Vandermeulen, D., and Suetens, P., "Automated model-based tissue classification of MR images of the brain.," IEEE Trans. Med. Imag. 18, 897-908 (1999).
5. Bezdek, J. C., Hall, L. O., and Clarke, L. P., "Review of MR image segmentation techniques using pattern recognition," Med. Phys. 20, 1033-1048 (1993).
6. Bezdek, J. C., [Pattern Recognition with Fuzzy Objective Function Algorithms], Plenum Press, New York (1981).
7. Xue, J.-H., Pižurica, A., Philips, W., Kerre, E., de Walle, R. V., and Lemahieu, I., "An integrated method of adaptive enhancement for unsupervised segmentation of MRI brain images," Pattern Recognition Letters 24, 2549-2560 (2003).
8. Ahmed, M. N., Yamany, S. M., Mohamed, N., Farag, A. A., and Moriaty, T., "A modified fuzzy c-means algorithm for bias field estimation and segmentation of MRI data," IEEE Trans. Med. Imag. 21, 193-199 (2002).
9. Zhang, D. and Chen, C., "A novel kernelized fuzzy c-means algorithm with application in medical image segmentation," Artificial Inteligence in Medicine 32, 37-50 (2004).
10. Shen, S., Sandham, W., Granat, M., and Sterr, A., "MRI fuzzy segmentation of brain tissue using neighborhood attraction with neural-network optimization," IEEE Trans. Inf. Technology in Biomedicine 9, 459-467 (2005).
11. Cai, W., Chen, S., and Zang, D., "Fast and robust fuzzy c-means clustering algorithms incorporating local information for image segmentation," Pattern Recognition 40, 825-838 (2007).
12. Wang, J., Kong, J., Lu, Y., Qi, M., and Zhang, B., "A modified FCM algorithm for MRI brain image segmentation using both local and non-local spatial constraints," Computerized Med. Imaging and Graphics 32, 685-698 (2008).
13. Pham, D. and Prince, J., "Adaptive fuzzy segmentation of Magnetic Resonance Images," IEEE Transactions on Medical Imaging 18(9), 737-752 (1999).
14. Elad, M., "On the origin of the bilateral filter and ways to improve it," IEEE Trans. Image Proc. 11, 1141-51 (2002).
15. Reddi, S. S., Rudin, S. F., and Keshavan, H. R., "An optical multiple threshold scheme for image segmentation," IEEE Trans. System Man Cybernet. 14, 661-665 (1984).
16. Collins, D. L., Zijdenbos, A. P., Kollokian, V., Sled, J. G., Kabani, N. J., Holmes, C. J., and Evans, A. C., "Design and construction of a realistic digital brain phantom," IEEE Trans. Med. Imag. 17, 463-468 (1998). http://www.bic.mni.mcgill.ca/brainweb/.