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Journal Abstract Search
552 related items for PubMed ID: 21233004
1. Evaluating intensity normalization on MRIs of human brain with multiple sclerosis. Shah M, Xiao Y, Subbanna N, Francis S, Arnold DL, Collins DL, Arbel T. Med Image Anal; 2011 Apr; 15(2):267-82. PubMed ID: 21233004 [Abstract] [Full Text] [Related]
3. Unifying framework for multimodal brain MRI segmentation based on Hidden Markov Chains. Bricq S, Collet Ch, Armspach JP. Med Image Anal; 2008 Dec; 12(6):639-52. PubMed ID: 18440268 [Abstract] [Full Text] [Related]
4. [Segmentation of multiple sclerosis lesions based on Markov random fields model for MR images]. Li B, Chen W. Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2009 Aug; 26(4):861-5. PubMed ID: 19813627 [Abstract] [Full Text] [Related]
5. Automatic detection of gadolinium-enhancing multiple sclerosis lesions in brain MRI using conditional random fields. Karimaghaloo Z, Shah M, Francis SJ, Arnold DL, Collins DL, Arbel T. IEEE Trans Med Imaging; 2012 Jun; 31(6):1181-94. PubMed ID: 22318484 [Abstract] [Full Text] [Related]
6. Performance-based classifier combination in atlas-based image segmentation using expectation-maximization parameter estimation. Rohlfing T, Russakoff DB, Maurer CR. IEEE Trans Med Imaging; 2004 Aug; 23(8):983-94. PubMed ID: 15338732 [Abstract] [Full Text] [Related]
9. Atlas-based fuzzy connectedness segmentation and intensity nonuniformity correction applied to brain MRI. Zhou Y, Bai J. IEEE Trans Biomed Eng; 2007 Jan; 54(1):122-9. PubMed ID: 17260863 [Abstract] [Full Text] [Related]
10. Brain tissue segmentation in MR images based on a hybrid of MRF and social algorithms. Yousefi S, Azmi R, Zahedi M. Med Image Anal; 2012 May; 16(4):840-8. PubMed ID: 22377656 [Abstract] [Full Text] [Related]
13. An accurate and efficient bayesian method for automatic segmentation of brain MRI. Marroquin JL, Vemuri BC, Botello S, Calderon F, Fernandez-Bouzas A. IEEE Trans Med Imaging; 2002 Aug; 21(8):934-45. PubMed ID: 12472266 [Abstract] [Full Text] [Related]
14. Method to correct intensity inhomogeneity in MR images for atherosclerosis characterization. Salvado O, Hillenbrand C, Zhang S, Wilson DL. IEEE Trans Med Imaging; 2006 May; 25(5):539-52. PubMed ID: 16689259 [Abstract] [Full Text] [Related]
15. A fully automated algorithm under modified FCM framework for improved brain MR image segmentation. Sikka K, Sinha N, Singh PK, Mishra AK. Magn Reson Imaging; 2009 Sep; 27(7):994-1004. PubMed ID: 19395212 [Abstract] [Full Text] [Related]
16. Automatic cerebral and cerebellar hemisphere segmentation in 3D MRI: adaptive disconnection algorithm. Zhao L, Ruotsalainen U, Hirvonen J, Hietala J, Tohka J. Med Image Anal; 2010 Jun; 14(3):360-72. PubMed ID: 20303318 [Abstract] [Full Text] [Related]
17. A modified possibilistic fuzzy c-means clustering algorithm for bias field estimation and segmentation of brain MR image. Ji ZX, Sun QS, Xia DS. Comput Med Imaging Graph; 2011 Jul; 35(5):383-97. PubMed ID: 21256710 [Abstract] [Full Text] [Related]