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  Longitudinal multiple sclerosis lesion segmentation: Resource and challenge

Carass, A., Roy, S., Jog, A., Cuzzocreo, J. L., Magrath, E., Gherman, A., et al. (2017). Longitudinal multiple sclerosis lesion segmentation: Resource and challenge. NeuroImage, 148, 77-102. doi:10.1016/j.neuroimage.2016.12.064.

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Genre: Zeitschriftenartikel

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externe Referenz:
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5344762/ (beliebiger Volltext)
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Grün

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 Urheber:
Carass, Aaron1, Autor
Roy, Snehashis1, Autor
Jog, Amod1, Autor
Cuzzocreo, Jennifer L.1, Autor
Magrath, Elizabeth1, Autor
Gherman, Adrian1, Autor
Button, Julia1, Autor
Nguyen, James1, Autor
Prados, Ferran1, Autor
Sudre, Carole E.1, Autor
Cardoso, Manuel Jorge1, Autor
Cawley, Niamh1, Autor
Ciccarelli, Olga1, Autor
Wheeler-Kingshott, Claudia A.M.1, Autor
Ourselin, Sébastien1, Autor
Catanese, Laurence1, Autor
Deshpande, Hrishikesh1, Autor
Maurel, Pierre1, Autor
Commowick, Oliver1, Autor
Barillot, Christian1, Autor
Tomas-Fernandez, Xavier1, AutorWarfield, Simon K.1, AutorVaidya, Suthirth1, AutorChunduru, Abhijith1, AutorMuthuganapathy, Ramanathan1, AutorKrishnamurthi, Ganapathy1, AutorJesson, Andrew1, AutorArbel, Tal1, AutorMaier, Oskar1, AutorHandels, Heinz1, AutorIheme, Leonardo O.1, AutorUnay, Devrim1, AutorJain, Saurabh1, AutorSima, Diana M.1, AutorSmeets, Dirk1, AutorGhafoorian, Mohsen1, AutorPlatel, Bram1, AutorBirenbaum, Ariel1, AutorGreenspan, Hayit1, AutorBazin, Pierre-Louis2, Autor           Calabresi, Pater A.1, AutorCrainiceanu, Ciprian M.1, AutorEllingsen, Lotta M.1, AutorReich, Daniel S.1, AutorPrince, Jerry L.1, AutorPham, Dzung L.1, Autor mehr..
Affiliations:
1External Organizations, ou_persistent22              
2Department Neurophysics (Weiskopf), MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_2205649              

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Schlagwörter: Magnetic resonance imaging; Multiple sclerosi
 Zusammenfassung: In conjunction with the ISBI 2015 conference, we organized a longitudinal lesion segmentation challenge providing training and test data to registered participants. The training data consisted of five subjects with a mean of 4.4 time-points, and test data of fourteen subjects with a mean of 4.4 time-points. All 82 data sets had the white matter lesions associated with multiple sclerosis delineated by two human expert raters. Eleven teams submitted results using state-of-the-art lesion segmentation algorithms to the challenge, with ten teams presenting their results at the conference. We present a quantitative evaluation comparing the consistency of the two raters as well as exploring the performance of the eleven submitted results in addition to three other lesion segmentation algorithms. The challenge presented three unique opportunities: (1) the sharing of a rich data set; (2) collaboration and comparison of the various avenues of research being pursued in the community; and (3) a review and refinement of the evaluation metrics currently in use. We report on the performance of the challenge participants, as well as the construction and evaluation of a consensus delineation. The image data and manual delineations will continue to be available for download, through an evaluation website2 as a resource for future researchers in the area. This data resource provides a platform to compare existing methods in a fair and consistent manner to each other and multiple manual raters.

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Sprache(n): eng - English
 Datum: 2016-08-192016-12-192017-01-112017-03
 Publikationsstatus: Erschienen
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: DOI: 10.1016/j.neuroimage.2016.12.064
Anderer: Epub 2017
PMID: 28087490
PMC: PMC5344762
 Art des Abschluß: -

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Projektinformation

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Projektname : -
Grant ID : EP/I027084/1
Förderprogramm : -
Förderorganisation : Engineering & Physical Sciences Research Council (EPSRC)
Projektname : -
Grant ID : MR/J01107X/1
Förderprogramm : -
Förderorganisation : Medical Research Council UK (MRC)
Projektname : -
Grant ID : EP/I027084/1
Förderprogramm : -
Förderorganisation : Engineering & Physical Sciences Research Council (EPSRC)

Quelle 1

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Titel: NeuroImage
Genre der Quelle: Zeitschrift
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: Orlando, FL : Academic Press
Seiten: - Band / Heft: 148 Artikelnummer: - Start- / Endseite: 77 - 102 Identifikator: ISSN: 1053-8119
CoNE: https://pure.mpg.de/cone/journals/resource/954922650166