Format
Sort by
Items per page

Send to

Choose Destination

Search results

Items: 1 to 20 of 35

1.

Objective Evaluation of Multiple Sclerosis Lesion Segmentation using a Data Management and Processing Infrastructure.

Commowick O, Istace A, Kain M, Laurent B, Leray F, Simon M, Pop SC, Girard P, Améli R, Ferré JC, Kerbrat A, Tourdias T, Cervenansky F, Glatard T, Beaumont J, Doyle S, Forbes F, Knight J, Khademi A, Mahbod A, Wang C, McKinley R, Wagner F, Muschelli J, Sweeney E, Roura E, Lladó X, Santos MM, Santos WP, Silva-Filho AG, Tomas-Fernandez X, Urien H, Bloch I, Valverde S, Cabezas M, Vera-Olmos FJ, Malpica N, Guttmann C, Vukusic S, Edan G, Dojat M, Styner M, Warfield SK, Cotton F, Barillot C.

Sci Rep. 2018 Sep 12;8(1):13650. doi: 10.1038/s41598-018-31911-7.

2.

Measurement of pediatric regional cerebral blood flow from 6 months to 15 years of age in a clinical population.

Carsin-Vu A, Corouge I, Commowick O, Bouzillé G, Barillot C, Ferré JC, Proisy M.

Eur J Radiol. 2018 Apr;101:38-44. doi: 10.1016/j.ejrad.2018.02.003. Epub 2018 Feb 6.

PMID:
29571799
3.

USPIO-positive MS lesions are associated with greater tissue damage than gadolinium-positive-only lesions during 3-year follow-up.

Kerbrat A, Combès B, Commowick O, Maarouf A, Bannier E, Ferré JC, Tourbah A, Ranjeva JP, Barillot C, Edan G.

Mult Scler. 2017 Oct 1:1352458517736148. doi: 10.1177/1352458517736148. [Epub ahead of print]

PMID:
29064775
4.

Block-Matching Distortion Correction of Echo-Planar Images With Opposite Phase Encoding Directions.

Hedouin R, Commowick O, Bannier E, Scherrer B, Taquet M, Warfield SK, Barillot C.

IEEE Trans Med Imaging. 2017 May;36(5):1106-1115. doi: 10.1109/TMI.2016.2646920. Epub 2017 Jan 9.

PMID:
28092527
5.

Longitudinal multiple sclerosis lesion segmentation: Resource and challenge.

Carass A, Roy S, Jog A, Cuzzocreo JL, Magrath E, Gherman A, Button J, Nguyen J, Prados F, Sudre CH, Jorge Cardoso M, Cawley N, Ciccarelli O, Wheeler-Kingshott CAM, Ourselin S, Catanese L, Deshpande H, Maurel P, Commowick O, Barillot C, Tomas-Fernandez X, Warfield SK, Vaidya S, Chunduru A, Muthuganapathy R, Krishnamurthi G, Jesson A, Arbel T, Maier O, Handels H, Iheme LO, Unay D, Jain S, Sima DM, Smeets D, Ghafoorian M, Platel B, Birenbaum A, Greenspan H, Bazin PL, Calabresi PA, Crainiceanu CM, Ellingsen LM, Reich DS, Prince JL, Pham DL.

Neuroimage. 2017 Mar 1;148:77-102. doi: 10.1016/j.neuroimage.2016.12.064. Epub 2017 Jan 11.

6.

Imaging biomarkers in multiple Sclerosis: From image analysis to population imaging.

Barillot C, Edan G, Commowick O.

Med Image Anal. 2016 Oct;33:134-139. doi: 10.1016/j.media.2016.06.017. Epub 2016 Jun 15.

PMID:
27374128
7.

The DTI Challenge: Toward Standardized Evaluation of Diffusion Tensor Imaging Tractography for Neurosurgery.

Pujol S, Wells W, Pierpaoli C, Brun C, Gee J, Cheng G, Vemuri B, Commowick O, Prima S, Stamm A, Goubran M, Khan A, Peters T, Neher P, Maier-Hein KH, Shi Y, Tristan-Vega A, Veni G, Whitaker R, Styner M, Westin CF, Gouttard S, Norton I, Chauvin L, Mamata H, Gerig G, Nabavi A, Golby A, Kikinis R.

J Neuroimaging. 2015 Nov-Dec;25(6):875-82. doi: 10.1111/jon.12283. Epub 2015 Aug 11.

8.

Diffusion MRI abnormalities detection with orientation distribution functions: a multiple sclerosis longitudinal study.

Commowick O, Maarouf A, Ferré JC, Ranjeva JP, Edan G, Barillot C.

Med Image Anal. 2015 May;22(1):114-23. doi: 10.1016/j.media.2015.02.005. Epub 2015 Mar 20.

9.

OFSEP, a nationwide cohort of people with multiple sclerosis: Consensus minimal MRI protocol.

Cotton F, Kremer S, Hannoun S, Vukusic S, Dousset V; Imaging Working Group of the Observatoire Français de la Sclérose en Plaques.

J Neuroradiol. 2015 Jun;42(3):133-40. doi: 10.1016/j.neurad.2014.12.001. Epub 2015 Feb 7. Review.

10.

Predictive value of imaging markers at multiple sclerosis disease onset based on gadolinium- and USPIO-enhanced MRI and machine learning.

Crimi A, Commowick O, Maarouf A, Ferré JC, Bannier E, Tourbah A, Berry I, Ranjeva JP, Edan G, Barillot C.

PLoS One. 2014 Apr 1;9(4):e93024. doi: 10.1371/journal.pone.0093024. eCollection 2014.

11.

A mathematical framework for the registration and analysis of multi-fascicle models for population studies of the brain microstructure.

Taquet M, Scherrer B, Commowick O, Peters JM, Sahin M, Macq B, Warfield SK.

IEEE Trans Med Imaging. 2014 Feb;33(2):504-17. doi: 10.1109/TMI.2013.2289381. Epub 2013 Nov 6.

12.

Non-local robust detection of DTI white matter differences with small databases.

Commowick O, Stamm A.

Med Image Comput Comput Assist Interv. 2012;15(Pt 3):476-84.

13.

Registration and analysis of white matter group differences with a multi-fiber model.

Taquet M, Scherrer B, Commowick O, Peters J, Sahin M, Macq B, Warfield SK.

Med Image Comput Comput Assist Interv. 2012;15(Pt 3):313-20.

14.

Automated diffeomorphic registration of anatomical structures with rigid parts: application to dynamic cervical MRI.

Commowick O, Wiest-Daesslé N, Prima S.

Med Image Comput Comput Assist Interv. 2012;15(Pt 2):163-70.

15.

Adaptive multi-modal particle filtering for probabilistic white matter tractography.

Stamm A, Commowick O, Barillot C, Pérez P.

Inf Process Med Imaging. 2013;23:594-606.

PMID:
24684002
16.

Estimating a reference standard segmentation with spatially varying performance parameters: local MAP STAPLE.

Commowick O, Akhondi-Asl A, Warfield SK.

IEEE Trans Med Imaging. 2012 Aug;31(8):1593-606. doi: 10.1109/TMI.2012.2197406. Epub 2012 May 2.

17.

Voxel-based quantitative analysis of brain images from ¹⁸F-FDG PET with a block-matching algorithm for spatial normalization.

Person C, Louis-Dorr V, Poussier S, Commowick O, Malandain G, Maillard L, Wolf D, Gillet N, Roch V, Karcher G, Marie PY.

Clin Nucl Med. 2012 Mar;37(3):268-73. doi: 10.1097/RLU.0b013e3182443b2d.

PMID:
22310254
18.

Automated delineation of white matter fiber tracts with a multiple region-of-interest approach.

Suarez RO, Commowick O, Prabhu SP, Warfield SK.

Neuroimage. 2012 Feb 15;59(4):3690-700. doi: 10.1016/j.neuroimage.2011.11.043. Epub 2011 Nov 27.

19.

Evaluation of registration methods on thoracic CT: the EMPIRE10 challenge.

Murphy K, van Ginneken B, Reinhardt JM, Kabus S, Ding K, Deng X, Cao K, Du K, Christensen GE, Garcia V, Vercauteren T, Ayache N, Commowick O, Malandain G, Glocker B, Paragios N, Navab N, Gorbunova V, Sporring J, de Bruijne M, Han X, Heinrich MP, Schnabel JA, Jenkinson M, Lorenz C, Modat M, McClelland JR, Ourselin S, Muenzing SE, Viergever MA, De Nigris D, Collins DL, Arbel T, Peroni M, Li R, Sharp GC, Schmidt-Richberg A, Ehrhardt J, Werner R, Smeets D, Loeckx D, Song G, Tustison N, Avants B, Gee JC, Staring M, Klein S, Stoel BC, Urschler M, Werlberger M, Vandemeulebroucke J, Rit S, Sarrut D, Pluim JP.

IEEE Trans Med Imaging. 2011 Nov;30(11):1901-20. doi: 10.1109/TMI.2011.2158349. Epub 2011 May 31.

PMID:
21632295
20.

Construction of patient specific atlases from locally most similar anatomical pieces.

Ramus L, Commowick O, Malandain G.

Med Image Comput Comput Assist Interv. 2010;13(Pt 3):155-62.

Supplemental Content

Loading ...
Support Center