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Similar articles for PubMed (Select 24505805)

1.

Minimizing joint risk of mislabeling for iterative Patch-based label fusion.

Wu G, Wang Q, Liao S, Zhang D, Nie F, Shen D.

Med Image Comput Comput Assist Interv. 2013;16(Pt 3):551-8.

2.

A generative probability model of joint label fusion for multi-atlas based brain segmentation.

Wu G, Wang Q, Zhang D, Nie F, Huang H, Shen D.

Med Image Anal. 2014 Aug;18(6):881-90. doi: 10.1016/j.media.2013.10.013. Epub 2013 Nov 16.

PMID:
24315359
3.

Hierarchical label fusion with multiscale feature representation and label-specific patch partition.

Wu G, Shen D.

Med Image Comput Comput Assist Interv. 2014;17(Pt 1):299-306.

PMID:
25333131
4.

A unified framework for cross-modality multi-atlas segmentation of brain MRI.

Eugenio Iglesias J, Rory Sabuncu M, Van Leemput K.

Med Image Anal. 2013 Dec;17(8):1181-91. doi: 10.1016/j.media.2013.08.001. Epub 2013 Aug 19.

5.

Hierarchical multi-atlas label fusion with multi-scale feature representation and label-specific patch partition.

Wu G, Kim M, Sanroma G, Wang Q, Munsell BC, Shen D; Alzheimer's Disease Neuroimaging Initiative.

Neuroimage. 2015 Feb 1;106:34-46. doi: 10.1016/j.neuroimage.2014.11.025. Epub 2014 Nov 20.

PMID:
25463474
6.

Optimal weights for multi-atlas label fusion.

Wang H, Suh JW, Pluta J, Altinay M, Yushkevich P.

Inf Process Med Imaging. 2011;22:73-84.

7.

Multi-atlas segmentation without registration: a supervoxel-based approach.

Wang H, Yushkevich PA.

Med Image Comput Comput Assist Interv. 2013;16(Pt 3):535-42.

8.

Multi-atlas segmentation with robust label transfer and label fusion.

Wang H, Pouch A, Takabe M, Jackson B, Gorman J, Gorman R, Yushkevich PA.

Inf Process Med Imaging. 2013;23:548-59.

9.

Multi-Atlas Segmentation with Joint Label Fusion.

Wang H, Suh JW, Das SR, Pluta J, Craige C, Yushkevich PA.

IEEE Trans Pattern Anal Mach Intell. 2012 Jun 22. [Epub ahead of print]

10.

Atlas encoding by randomized forests for efficient label propagation.

Zikic D, Glocker B, Criminisi A.

Med Image Comput Comput Assist Interv. 2013;16(Pt 3):66-73.

PMID:
24505745
11.

Deformable atlas for multi-structure segmentation.

Liu X, Montillo A, Tan ET, Schenck JF, Mendonca P.

Med Image Comput Comput Assist Interv. 2013;16(Pt 1):743-50.

PMID:
24505734
12.

Local label learning (LLL) for subcortical structure segmentation: application to hippocampus segmentation.

Hao Y, Wang T, Zhang X, Duan Y, Yu C, Jiang T, Fan Y; Alzheimer's Disease Neuroimaging Initiative.

Hum Brain Mapp. 2014 Jun;35(6):2674-97. doi: 10.1002/hbm.22359. Epub 2013 Oct 23.

PMID:
24151008
13.

Confidence-guided sequential label fusion for multi-atlas based segmentation.

Zhang D, Wu G, Jia H, Shen D.

Med Image Comput Comput Assist Interv. 2011;14(Pt 3):643-50.

PMID:
22003754
14.

Adaptive local multi-atlas segmentation: application to the heart and the caudate nucleus.

van Rikxoort EM, Isgum I, Arzhaeva Y, Staring M, Klein S, Viergever MA, Pluim JP, van Ginneken B.

Med Image Anal. 2010 Feb;14(1):39-49. doi: 10.1016/j.media.2009.10.001. Epub 2009 Oct 13.

PMID:
19897403
15.

Performance-based classifier combination in atlas-based image segmentation using expectation-maximization parameter estimation.

Rohlfing T, Russakoff DB, Maurer CR Jr.

IEEE Trans Med Imaging. 2004 Aug;23(8):983-94.

PMID:
15338732
16.

Non-local statistical label fusion for multi-atlas segmentation.

Asman AJ, Landman BA.

Med Image Anal. 2013 Feb;17(2):194-208. doi: 10.1016/j.media.2012.10.002. Epub 2012 Nov 29.

17.

Groupwise segmentation with multi-atlas joint label fusion.

Wang H, Yushkevich PA.

Med Image Comput Comput Assist Interv. 2013;16(Pt 1):711-8.

18.

Multi-atlas based segmentation of brain images: atlas selection and its effect on accuracy.

Aljabar P, Heckemann RA, Hammers A, Hajnal JV, Rueckert D.

Neuroimage. 2009 Jul 1;46(3):726-38. doi: 10.1016/j.neuroimage.2009.02.018. Epub 2009 Feb 23.

PMID:
19245840
19.
20.

A probabilistic, non-parametric framework for inter-modality label fusion.

Iglesias JE, Sabuncu MR, Van Leemput K.

Med Image Comput Comput Assist Interv. 2013;16(Pt 3):576-83.

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