Longitudinal multiple sclerosis lesion segmentation data resource

Carass, Aaron; Roy, Snehashis; Jog, Amod; Cuzzocreo, Jennifer L.; Magrath, Elizabeth; Gherman, Adrian; Button, Julia; Nguyen, James; Bazin, Pierre-Louis; Calabresi, Peter A.; Crainiceanu, Ciprian M.; Ellingsen, Lotta M.; Reich, Daniel S.; Prince, Jerry L.; Pham, Dzung L.

doi:10.1016/j.dib.2017.04.004

Item

ITEM ACTIONSEXPORT

Add to Basket

Please note that a newer version of this item is available:
https://pure.mpg.de/pubman/item/item_3169654_3

DetailsSummary

Released

Journal Article

Longitudinal multiple sclerosis lesion segmentation data resource

MPS-Authors

/persons/resource/persons23475

Bazin, Pierre-Louis
Department Neurophysics, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

External Resource

No external resources are shared

Fulltext (restricted access)

There are currently no full texts shared for your IP range.

Fulltext (public)

There are no public fulltexts stored in PuRe

Supplementary Material (public)

There is no public supplementary material available

Citation

Carass, A., Roy, S., Jog, A., Cuzzocreo, J. L., Magrath, E., Gherman, A., et al. (2017). Longitudinal multiple sclerosis lesion segmentation data resource. Data in Brief, 12, 346-350. doi:10.1016/j.dib.2017.04.004.

Cite as: https://hdl.handle.net/21.11116/0000-0004-DB5E-D

Abstract

The data presented in this article is related to the research article entitled “Longitudinal multiple sclerosis lesion segmentation: Resource and challenge” (Carass et al., 2017) [1]. In conjunction with the 2015 International Symposium on Biomedical Imaging, we organized a longitudinal multiple sclerosis (MS) lesion segmentation challenge providing training and test data to registered participants. The training data consists of five subjects with a mean of 4.4 (±0.55) time-points, and test data of fourteen subjects with a mean of 4.4 (±0.67) time-points. All 82 data sets had the white matter lesions associated with multiple sclerosis delineated by two human expert raters. The training data including multi-modal scans and manually delineated lesion masks is available for download.1 In addition, the testing data is also being made available in conjunction with a website for evaluating the automated analysis of the testing data.