The DOI matches its Crossref record; 106 of the 106 references it cites were found in a registry or an index.
Longitudinal multiple sclerosis lesion segmentation: Resource and challenge
Open accessAbstract
Abstract 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. HighlightsPublic lesion data base of 21 training data sets and 61 testing data sets.Fully automated evaluation website.Comparison between 14 state‐of‐the‐art algorithms and 2 manual delineators.
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Self-citationN4ITK: Improved N3 Bias Correction
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Self-citationConvolutional neural networks for multi-class brain disease detection using MRI images
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Metadata
- Authors
- Carass, A., Roy, S., Jog, A., Cuzzocreo, J. L., Magrath, E., Gherman, A., Button, J., Nguyen, J., Prados, F., Sudre, C. H., Jorge Cardoso, M., Cawley, N., Ciccarelli, O., Wheeler-Kingshott, C. A. M., Ourselin, S., Catanese, L., Deshpande, H., Maurel, P., Commowick, O., Barillot, C., Tomas-Fernandez, X., Warfield, S. K., Vaidya, S., Chunduru, A., Muthuganapathy, R., Krishnamurthi, G., Jesson, A., Arbel, T., Maier, O., Handels, H., Iheme, L. O., Unay, D., Jain, S., Sima, D. M., Smeets, D., Ghafoorian, M., Platel, B., Birenbaum, A., Greenspan, H., Bazin, P.-L., Calabresi, P. A., Crainiceanu, C. M., Ellingsen, L. M., Reich, D. S., Prince, J. L., & Pham, D. L.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2017-03
- Volume
- 148
- Pages
- 77-102
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W2575552683
- Cited by
- 357
- References
- 106
- FWCI
- 13.14
- Type
- journal article
- Language
- en
- Open access
- green
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- Carass, A., Roy, S., Jog, A., Cuzzocreo, J. L., Magrath, E., Gherman, A., Button, J., Nguyen, J., Prados, F., Sudre, C. H., Jorge Cardoso, M., Cawley, N., Ciccarelli, O., Wheeler-Kingshott, C. A. M., Ourselin, S., Catanese, L., Deshpande, H., Maurel, P., Commowick, O., . . . Pham, D. L. (2017). Longitudinal multiple sclerosis lesion segmentation: Resource and challenge. NeuroImage. https://doi.org/10.1016/j.neuroimage.2016.12.064
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