Multi-stage FCM-based intensity inhomogeneity correction for MR brain image segmentation

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5164 LNCS, Issue PART 2, 2008, Pages 527-536

  Szilágyi, László ^a,b   Szilágyi, Sándor M ^b   Dávid, László ^b   Benyó, Zoltán ^a  

^a BUDAPEST UNIVERSITY OF TECHNOLOGY AND ECONOMICS   (Hungary)

^b SAPIENTIA HUNGARIAN UNIVERSITY OF TRANSYLVANIA   (Romania)

Author keywords

Context dependent filter; Fuzzy c means algorithm; Image segmentation; Intensity inhomogeneity; Magnetic resonance imaging; Morphological operations

Indexed keywords

ARTIFICIAL INTELLIGENCE; BACKPROPAGATION; CLUSTERING ALGORITHMS; COMPUTERIZED TOMOGRAPHY; DIGITAL IMAGE STORAGE; FOOD ADDITIVES; FUZZY RULES; FUZZY SYSTEMS; IMAGE PROCESSING; IMAGE SEGMENTATION; THREE DIMENSIONAL;

3-D REGISTRATION; ARTIFICIAL NEURAL NETWORKS; CONTEXT DEPENDENT FILTER; CONTEXT-DEPENDENT; FUZZY C-MEANS; FUZZY C-MEANS ALGORITHM; FUZZY MEMBERSHIP VALUES; GAUSSIAN; HIGH AMPLITUDES; INTENSITY INHOMOGENEITY; INTENSITY INHOMOGENEITY CORRECTION; INTERNATIONAL CONFERENCES; MAGNETIC RESONANCE IMAGING; MORPHOLOGICAL OPERATIONS; MR BRAIN IMAGE SEGMENTATION; MR IMAGING; MULTI-STAGE; MULTIPLICATIVE NOISES; NOISE ELIMINATION; NON UNIFORMITIES; PRE-FILTERING; REGISTRATION METHODS; SEGMENTATION TECHNIQUES;

NEURAL NETWORKS;

EID: 51849157762     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-87559-8_55     Document Type: Conference Paper

References (19)

1. Ahmed, M.N., Yamany, S.M., Mohamed, N., Farag, A.A., Moriarty, T.: A modified fuzzy c-means algorithm for bias field estimation and segmentation of MRI data. IEEE Trans. Med. Imag. 21, 193-199 (2002)
2. Axel, L., Costanini, J., Listerud, J.: Inhomogeneity correction in surface-coil MR imaging. Amer. J. Roentgenol. 148, 418-420 (1987)
3. Bezdek, J.C., Pal, S.K.: Fuzzy models for pattern recognition. IEEE Press, Piscat-away (1991)
4. Brinkmann, B.H., Manduca, A., Robb, R.A.: Optimized homomorphic unsharp masking for MR grayscale inhomogeneity correction. IEEE Trans. Med. Imag. 17, 161-171 (1998)
5. Cai, W., Chen, S., Zhang, D.Q.: Fast and robust fuzzy c-means algorithms incorporating local information for image segmentation. Patt. Recogn. 40, 825-838 (2007)
6. Internet Brain Segmentation Repository, http://www.cma.mgh.harvard.edu/ ibsr
7. Johnston, B., Atkins, M.S., Mackiewich, B., Anderson, M.: Segmentation of multiple sclerosis lesions in intensity corrected multispectral MRI. IEEE Trans. Med. Imag. 15, 154-169 (1996)
8. Leemput, K.V., Maes, F., Vandermeulen, D., Suetens, P.: Automated model-based bias field correction of MR images of the brain. IEEE Trans. Med. Imag. 18, 885- 896 (1999)
9. Li, X., Li, L.H., Lu, H.B., Liang, Z.G.: Partial volume segmentation of brain magnetic resonace images based on maximum a posteriori probability. Med. Phys. 32, 2337-2345 (2005)
10. Liew, A.W.C., Hong, Y.: An adaptive spatial fuzzy clustering algorithm for 3-D MR image segmentation. IEEE Trans. Med. Imag. 22, 1063-1075 (2003)
11. Nagy, L., Benyó, B.: Filtering and contrast enhancement on subtracted direct digital angiograms. In: Ann. Int. Conf. IEEE Eng. Med. Biol. Soc., vol. 26, pp. 1533- 1536. San Francisco (2004)
12. Pham, D.L., Prince, J.L.: An adaptive fuzzy C-means algorithm for image segmentation in the presence of intensity inhomogeneity. Patt. Recogn. Lett. 20, 57-68 (1999)
13. Pham, D.L., Prince, J.L.: Adaptive fuzzy segmentation of magnetic resonance images. IEEE Trans. Med. Imag. 18, 737-752 (1999)
14. Siyal, M.Y., Yu, L.: An intelligent modified fuzzy c-means based algorithm for bias field estimation and segmentation of brain MRI. Patt. Recogn. Lett. 26, 2052-2062 (2005)
15. Szilágyi, L.: Medical image processing methods for the development of a virtual endoscope. Period. Polytech. Ser. Electr. Eng. 50(1-2), 69-78 (2006)
16. Szilágyi, L., Szilágyi, S.M., Benyó, Z.: Efficient Feature Extraction for Fast Segmentation of MR Brain Images. In: Ersbøll, B.K., Pedersen, K.S. (eds.) SCIA 2007. LNCS, vol. 4522, pp. 611-620. Springer, Heidelberg (2007)
17. Vovk, U., Pernuš, F., Likar, B.: A review of methods for correction of intensity inhomogeneity in MRI. IEEE Trans. Med. Imag. 26, 405-421 (2007)
18. Wells, W.M., Grimson, W.E.L., Kikinis, R., Jolesz, F.A.: Adaptive segmentation of MRI data. IEEE Trans. Med. Imag. 15, 429-442 (1996)
19. Zhang, Y., Brady, M., Smith, S.: Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm. IEEE Trans. Med. Imag. 20, 45-57 (2001)