Prior knowledge driven multiscale segmentation of brain MRI

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

Volumn 4792 LNCS, Issue PART 2, 2007, Pages 118-126

  Akselrod Ballin, Ayelet ^a   Galun, Meirav ^a   Gomori, John Moshe ^b   Brandt, Achi ^a   Basri, Ronen ^a  

^a WEIZMANN INSTITUTE OF SCIENCE   (Israel)

^b HADASSAH HEBREW UNIVERSITY MEDICAL CENTER   (Israel)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; BAYESIAN NETWORKS; BRAIN; IMAGE SEGMENTATION; KNOWLEDGE ACQUISITION;

GOLD STANDARD; GRAPH REPRESENTATION; MULTISCALE ALGORITHMS;

MAGNETIC RESONANCE IMAGING;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BRAIN; COMPUTER ASSISTED DIAGNOSIS; EVALUATION; HISTOLOGY; HUMAN; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; THREE DIMENSIONAL IMAGING; VALIDATION STUDY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BRAIN; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; MAGNETIC RESONANCE IMAGING; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SUBTRACTION TECHNIQUE;

EID: 79551681002     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-75759-7_15     Document Type: Conference Paper

References (16)

1. Zijdenbos, A., Forghani, R., Evans, A.: Automatic pipeline analysis of 3D MRI data for clinical trials: application to MS. IEEE TMI 21(10), 1280-1291 (2002)
2. Pham, D., Xu, C., Prince, J.: Current methods in medical image segmentation. Annual Review of Biomedical Engineering 2, 315-337 (2000)
3. Sonka, M.M., Fitzpatrick, J.M. (eds.): Handbook of Medical Imaging. SPIE (2000)
4. Van-Leemput, K.: Probabilistic brain atlas encoding using bayesian inference. MICCAI 1, 704-711 (2006)
5. Pitiot, A., Delingette, H., Thompson, P.M., Ayache, N.: Expert knowledge guided segmentation system for brain MRI. NeuroImage 23(1), S85-S96 (2004)
6. Ciofolo, C., Barillot, C.: Brain segmentation with competitive level sets and fuzzy control. In: Christensen, G.E., Sonka, M. (eds.) IPMI 2005. LNCS, vol. 3565, pp. 333-344. Springer, Heidelberg (2005)
7. Pham, D., Prince, J.: Adaptive fuzzy segmentation of magnetic resonance images. IEEE TMI 18, 737-752 (1999)
8. Wells, W.M., Grimson, W., Kikinis, R., Jolesz, F.A.: Adaptive segmentation of MRI data. IEEE TMI 15, 429-442 (1996)
9. Pohl, K., Bouix, S., Kikinis, R., Grimson, W.: Anatomical guided segmentation with non-stationary tissue class distributions in an expectation-maximization framework. IBSI, 564-572 (2004)
10. Fischl, B., Salat, D., Busa, E., Albert, M., Dieterich, M., Haselgrove, C., van der Kouwe, A., Killiany, R., Kennedy, D., Klaveness, S.: Whole Brain Segmentatio-nAutomated Labeling of Neuroanatomical Structures in the Human Brain. Neuron 33(3), 341-355 (2002)
11. Akselrod-Ballin, A., Galun, M., Gomori, J.M., Basri, R., Brandt, A.: Atlas guided identification of brain structures by combining 3D segmentation and SVM classification. In: Larsen, R., Nielsen, M., Sporring, J. (eds.) MICCAI 2006. LNCS, vol. 4190, Springer, Heidelberg (2006)
12. Galun, M., Sharon, E., Basri, R., Brandt, A.: Texture segmentation by multiscale aggregation of filter responses and shape elements. In: ICCV, pp. 716-723 (2003)
13. Nain, D., Haker, S., Bobick, A., Tannenbaum, A.: Shape-driven 3D segmentation using spherical wavelets. In: Larsen, R., Nielsen, M., Sporring, J. (eds.) MICCAI 2006. LNCS, vol. 4190, Springer, Heidelberg (2006)
14. Smith, S.: Fast robust automated brain extraction. Human Brain Mapping 17(3), 143-155 (2002)
15. Woods, R., Grafton, S., Holmes, C., Cherry, S., Mazziotta, J.: Automated image registration: I. general methods and intrasubject, intramodality validation. Journal of Computer Assisted Tomography 22, 139-152 (1998)
16. Dawant, B.M., Hartmann, S.L., Thirion, J., Maes, F., Vandermeulen, D., Demaerel, P.: Automatic 3D segmentation of internal structures of the head in MRI using a combination of similarity and free-form transformations. IEEE TMI 18 (1999)