Model-based segmentation of hippocampal subfields in ultra-high resolution in vivo MRI

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

Volumn 5241 LNCS, Issue PART 1, 2008, Pages 235-243

  Van Leemput, Koen ^a,b   Bakkour, Akram ^a,c   Benner, Thomas ^a   Wiggins, Graham ^a   Wald, Lawrence L ^a,d   Augustinack, Jean ^a   Dickerson, Bradford C ^a,c   Golland, Polina ^b   Fischl, Bruce ^a,b,d  

^a HARVARD MEDICAL SCHOOL   (United States)

^b MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^c MASSACHUSETTS GENERAL HOSPITAL   (United States)

^d MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ANATOMICAL FEATURES; AUTOMATED METHODS; AUTOMATED SEGMENTATION; BAYESIAN APPROACHES; CLINICAL RESEARCH; COMPUTATIONAL MODEL; HIPPOCAMPAL FORMATION; HUMAN MEMORY; IN-VIVO; LEVEL OF DETAIL; MODEL-BASED SEGMENTATION; MRI SCAN; NEURO-IMAGING; SEGMENTATION RESULTS; SUBFIELDS; ULTRAHIGH RESOLUTION;

BAYESIAN NETWORKS; COMPUTER SCIENCE; IMAGE SEGMENTATION; SECURITY OF DATA; TECHNOLOGY TRANSFER;

MEDICAL COMPUTING;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; CLUSTER ANALYSIS; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; HIPPOCAMPUS; HISTOLOGY; HUMAN; IMAGE ENHANCEMENT; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CLUSTER ANALYSIS; COMPUTER SIMULATION; HIPPOCAMPUS; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MODELS, BIOLOGICAL; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 84858073727     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-85988-8_29     Document Type: Conference Paper

References (20)

1. Wells, W., et al.: Adaptive segmentation of MRI data. IEEE Transactions on Medical Imaging 15(4), 429-442 (1996)
2. Van Leemput, K., et al.: Automated model-based tissue classification of MR images of the brain. IEEE Transactions on Medical Imaging 18(10), 897-908 (1999)
3. Ashburner, J., Friston, K.: Unified segmentation. Neurolmage 26, 839-885 (2005)
4. Fischl, B., et al.: Whole brain segmentation: Automated labeling of neuroanatomical structures in the human brain. Neuron 33, 341-355 (2002)
5. Pohl, K., et al.: A Bayesian model for joint segmentation and registration. Neurolmage 31, 228-239 (2006)
6. Heckemann, R., et al.: Automatic anatomical brain MRI segmentation combining label propagation and decision fusion. Neurolmage 33(1), 115-126 (2006)
7. Wiggins, G., et al.: 32-channel 3 Tesla, receive-only phased-array head coil with soccer-ball element, geometry. Magn. Res. in Medicine 56(1), 216-223 (2006)
8. Zeineh, M., et al.: Dynamics of the Hippocampus During Encoding and Retrieval of Face-Name Pairs. Science 299(5606), 577-580 (2003)
9. Gabrieli, J., et al.: Separate Neural Bases of Two Fundamental Memory Processes in the Human Medial Temporal Lobe. Science 276(5310), 264 (1997)
10. Small, S., et al.: Evaluating the function of hippocampal subregions with high-resolution MRI in AD and aging. Microsc. Res. and Tech. 51(1), 101-108 (2000)
11. Shattuck, D., et al.: Construction of a 3D probabilistic atlas of human cortical structures. Neurolmage 39, 1064-1080 (2008)
12. Van Leemput, K.: Probabilistic brain atlas encoding using Bayesian inference. In: Larsen, R., Nielsen, M., Sporring, J. (eds.) MICCAI 2006. LNCS, vol. 4190, pp. 704-711. Springer, Heidelberg (2006)
13. Ashburner, et al.: Image registration using a symmetric prior-in three dimensions. Human Brain Mapping 9(4), 212-225 (2000)
14. Dempster, A.P., et al.: Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society 39, 1-38 (1977)
15. Stoica, P., Seién, Y.: Cyclic minimizers, majorization techniques, and the EM algorithm: A refresher. IEEE Signal Processing Magazine, 112-114 (2004)
16. Minka, T.: Expectation-Maximization as lower bound maximization. Technical report, MIT (1998)
17. D'Agostino, E., et al.: A unified framework for atlas based brain image segmentation and registration. In: Pluim, J.P.W., Likar, B., Gerritsen, F.A. (eds.) WBIR 2006. LNCS, vol. 4057, pp. 136-143. Springer, Heidelberg (2006)
18. Wells, W., et al.: Multi-modal volume registration by maximization of mutual information. Medical Image Analysis 1(1), 35-51 (1996)
19. Maes, F., et al.: Multimodality image registration by maximization of mutual information. IEEE Transactions on Medical Imaging 16(2), 187-198 (1997)
20. Van Leemput, K., et al.: A unifying framework for partial volume segmentation of brain MR images. IEEE Transactions on Medical Imaging 22(1), 105-119 (2003)