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Items: 1 to 20 of 146


Improving intersubject image registration using tissue-class information benefits robustness and accuracy of multi-atlas based anatomical segmentation.

Heckemann RA, Keihaninejad S, Aljabar P, Rueckert D, Hajnal JV, Hammers A; Alzheimer's Disease Neuroimaging Initiative.

Neuroimage. 2010 May 15;51(1):221-7. doi: 10.1016/j.neuroimage.2010.01.072. Epub 2010 Jan 28.


Multi-atlas segmentation of the whole hippocampus and subfields using multiple automatically generated templates.

Pipitone J, Park MT, Winterburn J, Lett TA, Lerch JP, Pruessner JC, Lepage M, Voineskos AN, Chakravarty MM; Alzheimer's Disease Neuroimaging Initiative.

Neuroimage. 2014 Nov 1;101:494-512. doi: 10.1016/j.neuroimage.2014.04.054. Epub 2014 Apr 29.


LEAP: learning embeddings for atlas propagation.

Wolz R, Aljabar P, Hajnal JV, Hammers A, Rueckert D; Alzheimer's Disease Neuroimaging Initiative.

Neuroimage. 2010 Jan 15;49(2):1316-25. doi: 10.1016/j.neuroimage.2009.09.069. Epub 2009 Oct 6.


A direct morphometric comparison of five labeling protocols for multi-atlas driven automatic segmentation of the hippocampus in Alzheimer's disease.

Nestor SM, Gibson E, Gao FQ, Kiss A, Black SE; Alzheimer's Disease Neuroimaging Initiative.

Neuroimage. 2013 Feb 1;66:50-70. doi: 10.1016/j.neuroimage.2012.10.081. Epub 2012 Nov 7.


A multi-atlas based method for automated anatomical Macaca fascicularis brain MRI segmentation and PET kinetic extraction.

Ballanger B, Tremblay L, Sgambato-Faure V, Beaudoin-Gobert M, Lavenne F, Le Bars D, Costes N.

Neuroimage. 2013 Aug 15;77:26-43. doi: 10.1016/j.neuroimage.2013.03.029. Epub 2013 Mar 26.


Measurement of hippocampal atrophy using 4D graph-cut segmentation: application to ADNI.

Wolz R, Heckemann RA, Aljabar P, Hajnal JV, Hammers A, Lötjönen J, Rueckert D; Alzheimer's Disease Neuroimaging Initiative.

Neuroimage. 2010 Aug 1;52(1):109-18. doi: 10.1016/j.neuroimage.2010.04.006. Epub 2010 Apr 9.


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.


View-centralized multi-atlas classification for Alzheimer's disease diagnosis.

Liu M, Zhang D, Shen D; Alzheimer's Disease Neuroimaging Initiative.

Hum Brain Mapp. 2015 May;36(5):1847-65. doi: 10.1002/hbm.22741. Epub 2015 Jan 27.


A learning-based wrapper method to correct systematic errors in automatic image segmentation: consistently improved performance in hippocampus, cortex and brain segmentation.

Wang H, Das SR, Suh JW, Altinay M, Pluta J, Craige C, Avants B, Yushkevich PA; Alzheimer's Disease Neuroimaging Initiative.

Neuroimage. 2011 Apr 1;55(3):968-85. doi: 10.1016/j.neuroimage.2011.01.006. Epub 2011 Jan 13.


Using manifold learning for atlas selection in multi-atlas segmentation.

Hoang Duc AK, Modat M, Leung KK, Cardoso MJ, Barnes J, Kadir T, Ourselin S; Alzheimer’s Disease Neuroimaging Initiative.

PLoS One. 2013 Aug 2;8(8):e70059. doi: 10.1371/journal.pone.0070059. Print 2013.


Robust whole-brain segmentation: application to traumatic brain injury.

Ledig C, Heckemann RA, Hammers A, Lopez JC, Newcombe VF, Makropoulos A, Lötjönen J, Menon DK, Rueckert D.

Med Image Anal. 2015 Apr;21(1):40-58. doi: 10.1016/ Epub 2014 Dec 24.


A computational atlas of the hippocampal formation using ex vivo, ultra-high resolution MRI: Application to adaptive segmentation of in vivo MRI.

Iglesias JE, Augustinack JC, Nguyen K, Player CM, Player A, Wright M, Roy N, Frosch MP, McKee AC, Wald LL, Fischl B, Van Leemput K; Alzheimer's Disease Neuroimaging Initiative.

Neuroimage. 2015 Jul 15;115:117-37. doi: 10.1016/j.neuroimage.2015.04.042. Epub 2015 Apr 29.


A topology-preserving approach to the segmentation of brain images with multiple sclerosis lesions.

Shiee N, Bazin PL, Ozturk A, Reich DS, Calabresi PA, Pham DL.

Neuroimage. 2010 Jan 15;49(2):1524-35. doi: 10.1016/j.neuroimage.2009.09.005. Epub 2009 Sep 17.


Fast and robust multi-atlas segmentation of brain magnetic resonance images.

Lötjönen JM, Wolz R, Koikkalainen JR, Thurfjell L, Waldemar G, Soininen H, Rueckert D; Alzheimer's Disease Neuroimaging Initiative.

Neuroimage. 2010 Feb 1;49(3):2352-65. doi: 10.1016/j.neuroimage.2009.10.026. Epub 2009 Oct 24.


Automated algorithm to measure changes in medial temporal lobe volume in Alzheimer disease.

Kazemifar S, Drozd JJ, Rajakumar N, Borrie MJ, Bartha R; Alzheimer's Disease Neuroimaging Initiative.

J Neurosci Methods. 2014 Apr 30;227:35-46. doi: 10.1016/j.jneumeth.2014.01.033. Epub 2014 Feb 8.


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.


Multi-atlas based representations for Alzheimer's disease diagnosis.

Min R, Wu G, Cheng J, Wang Q, Shen D; Alzheimer's Disease Neuroimaging Initiative.

Hum Brain Mapp. 2014 Oct;35(10):5052-70. doi: 10.1002/hbm.22531. Epub 2014 Apr 18.


A fast atlas pre-selection procedure for multi-atlas based brain segmentation.

Ma J, Ma HT, Li H, Ye C, Wu D, Tang X, Miller M, Mori S.

Conf Proc IEEE Eng Med Biol Soc. 2015;2015:3053-6. doi: 10.1109/EMBC.2015.7319036.


Improved segmentation of cerebellar structures in children.

Narayanan PL, Warton C, Rosella Boonzaier N, Molteno CD, Joseph J, Jacobson JL, Jacobson SW, Zöllei L, Meintjes EM.

J Neurosci Methods. 2016 Mar 15;262:1-13. doi: 10.1016/j.jneumeth.2015.12.010. Epub 2015 Dec 29.


MUSE: MUlti-atlas region Segmentation utilizing Ensembles of registration algorithms and parameters, and locally optimal atlas selection.

Doshi J, Erus G, Ou Y, Resnick SM, Gur RC, Gur RE, Satterthwaite TD, Furth S, Davatzikos C; Alzheimer's Neuroimaging Initiative.

Neuroimage. 2016 Feb 15;127:186-195. doi: 10.1016/j.neuroimage.2015.11.073. Epub 2015 Dec 8.

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