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Items: 1 to 20 of 118

1.

Incorporating parameter uncertainty in Bayesian segmentation models: application to hippocampal subfield volumetry.

Iglesias JE, Sabuncu MR, Van Leemput K; Alzheimer's Disease Neuroimaging Initiative.

Med Image Comput Comput Assist Interv. 2012;15(Pt 3):50-7.

2.

Improved inference in Bayesian segmentation using Monte Carlo sampling: application to hippocampal subfield volumetry.

Iglesias JE, Sabuncu MR, Van Leemput K; Alzheimer’s Disease Neuroimaging Initiative.

Med Image Anal. 2013 Oct;17(7):766-78. doi: 10.1016/j.media.2013.04.005. Epub 2013 May 22.

3.

Anatomically constrained region deformation for the automated segmentation of the hippocampus and the amygdala: Method and validation on controls and patients with Alzheimer's disease.

Chupin M, Mukuna-Bantumbakulu AR, Hasboun D, Bardinet E, Baillet S, Kinkingnéhun S, Lemieux L, Dubois B, Garnero L.

Neuroimage. 2007 Feb 1;34(3):996-1019. Epub 2006 Dec 18.

PMID:
17178234
4.

Hippocampal volume change measurement: quantitative assessment of the reproducibility of expert manual outlining and the automated methods FreeSurfer and FIRST.

Mulder ER, de Jong RA, Knol DL, van Schijndel RA, Cover KS, Visser PJ, Barkhof F, Vrenken H; Alzheimer's Disease Neuroimaging Initiative.

Neuroimage. 2014 May 15;92:169-81. doi: 10.1016/j.neuroimage.2014.01.058. Epub 2014 Feb 9.

PMID:
24521851
5.

Multilevel segmentation and integrated bayesian model classification with an application to brain tumor segmentation.

Corso JJ, Sharon E, Yuille A.

Med Image Comput Comput Assist Interv. 2006;9(Pt 2):790-8.

PMID:
17354845
6.

Validation of a fully automated 3D hippocampal segmentation method using subjects with Alzheimer's disease mild cognitive impairment, and elderly controls.

Morra JH, Tu Z, Apostolova LG, Green AE, Avedissian C, Madsen SK, Parikshak N, Hua X, Toga AW, Jack CR Jr, Weiner MW, Thompson PM; Alzheimer's Disease Neuroimaging Initiative.

Neuroimage. 2008 Oct 15;43(1):59-68. doi: 10.1016/j.neuroimage.2008.07.003. Epub 2008 Jul 16. Erratum in: Neuroimage. 2009 Feb 15;44(4):1439.

7.

Bayesian segmentation of human facial tissue using 3D MR-CT information fusion, resolution enhancement and partial volume modelling.

Şener E, Mumcuoglu EU, Hamcan S.

Comput Methods Programs Biomed. 2016 Feb;124:31-44. doi: 10.1016/j.cmpb.2015.10.009. Epub 2015 Oct 23.

PMID:
26574298
8.

Hierarchical bayesian modeling, estimation, and sampling for multigroup shape analysis.

Yu YY, Fletcher PT, Awate SP.

Med Image Comput Comput Assist Interv. 2014;17(Pt 3):9-16.

9.

STEPS: Similarity and Truth Estimation for Propagated Segmentations and its application to hippocampal segmentation and brain parcelation.

Jorge Cardoso M, Leung K, Modat M, Keihaninejad S, Cash D, Barnes J, Fox NC, Ourselin S; Alzheimer’s Disease Neuroimaging Initiative.

Med Image Anal. 2013 Aug;17(6):671-84. doi: 10.1016/j.media.2013.02.006. Epub 2013 Mar 1.

10.

Hippocampus segmentation in MR images using atlas registration, voxel classification, and graph cuts.

van der Lijn F, den Heijer T, Breteler MM, Niessen WJ.

Neuroimage. 2008 Dec;43(4):708-20. doi: 10.1016/j.neuroimage.2008.07.058. Epub 2008 Aug 12.

PMID:
18761411
11.

Evaluation of group-specific, whole-brain atlas generation using Volume-based Template Estimation (VTE): application to normal and Alzheimer's populations.

Zhang Y, Zhang J, Hsu J, Oishi K, Faria AV, Albert M, Miller MI, Mori S.

Neuroimage. 2014 Jan 1;84:406-19. doi: 10.1016/j.neuroimage.2013.09.011. Epub 2013 Sep 16.

12.

Can voxel based morphometry, manual segmentation and automated segmentation equally detect hippocampal volume differences in acute depression?

Bergouignan L, Chupin M, Czechowska Y, Kinkingnéhun S, Lemogne C, Le Bastard G, Lepage M, Garnero L, Colliot O, Fossati P.

Neuroimage. 2009 Mar 1;45(1):29-37. doi: 10.1016/j.neuroimage.2008.11.006. Epub 2008 Nov 21.

PMID:
19071222
13.

Automatic hippocampus segmentation of 7.0 Tesla MR images by combining multiple atlases and auto-context models.

Kim M, Wu G, Li W, Wang L, Son YD, Cho ZH, Shen D.

Neuroimage. 2013 Dec;83:335-45. doi: 10.1016/j.neuroimage.2013.06.006. Epub 2013 Jun 11.

14.

Bayesian longitudinal segmentation of hippocampal substructures in brain MRI using subject-specific atlases.

Iglesias JE, Van Leemput K, Augustinack J, Insausti R, Fischl B, Reuter M; Alzheimer's Disease Neuroimaging Initiative.

Neuroimage. 2016 Nov 1;141:542-555. doi: 10.1016/j.neuroimage.2016.07.020. Epub 2016 Jul 15.

15.

Multi-atlas Segmentation as a Graph Labelling Problem: Application to Partially Annotated Atlas Data.

Koch LM, Rajchl M, Tong T, Passerat-Palmbach J, Aljabar P, Rueckert D.

Inf Process Med Imaging. 2015;24:221-32.

PMID:
26221676
16.

Discrimination between Alzheimer disease, mild cognitive impairment, and normal aging by using automated segmentation of the hippocampus.

Colliot O, Chételat G, Chupin M, Desgranges B, Magnin B, Benali H, Dubois B, Garnero L, Eustache F, Lehéricy S.

Radiology. 2008 Jul;248(1):194-201. doi: 10.1148/radiol.2481070876. Epub 2008 May 5.

PMID:
18458242
17.

Surface-based multi-template automated hippocampal segmentation: application to temporal lobe epilepsy.

Kim H, Mansi T, Bernasconi N, Bernasconi A.

Med Image Anal. 2012 Oct;16(7):1445-55. doi: 10.1016/j.media.2012.04.008. Epub 2012 May 3.

PMID:
22613821
18.

Hippocampal shape classification using redundancy constrained feature selection.

Zhou L, Wang L, Shen C, Barnes N.

Med Image Comput Comput Assist Interv. 2010;13(Pt 2):266-73.

PMID:
20879324
19.

Prior shape level set segmentation on multistep generated probability maps of MR datasets for fully automatic kidney parenchyma volumetry.

Gloger O, Tönies KD, Liebscher V, Kugelmann B, Laqua R, Völzke H.

IEEE Trans Med Imaging. 2012 Feb;31(2):312-25. doi: 10.1109/TMI.2011.2168609. Epub 2011 Sep 19.

PMID:
21937343
20.

Fully automatic segmentation of the hippocampus and the amygdala from MRI using hybrid prior knowledge.

Chupin M, Hammers A, Bardinet E, Colliot O, Liu RS, Duncan JS, Garnero L, Lemieux L.

Med Image Comput Comput Assist Interv. 2007;10(Pt 1):875-82.

PMID:
18051141

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