Longitudinal multiple sclerosis lesion segmentation: Resource and challenge
Aaron Carass
(1, 2)
,
Snehashis Roy
(3)
,
Amod Jog
(1)
,
Jennifer L. Cuzzocreo
(4)
,
Elizabeth Magrath
(3)
,
Adrian Gherman
(2)
,
Julia Button
(4)
,
James Nguyen
(4)
,
Ferran Prados
(5, 6)
,
Carole H. Sudre
(6)
,
Manuel Jorge Cardoso
(7, 6)
,
Niamh Cawley
(5)
,
Olga Ciccarelli
(5)
,
Claudia A.M. Wheeler-Kingshott
(5)
,
Sébastien Ourselin
(6, 7)
,
Laurence Catanese
(8)
,
Hrishikesh Deshpande
(9)
,
Pierre Maurel
(9)
,
Olivier Commowick
(9)
,
Christian Barillot
(9)
,
Xavier Tomas-Fernandez
(10)
,
Simon K. Warfield
(10)
,
Suthirth Vaidya
(11)
,
Abhijith Chunduru
(11)
,
Ramanathan Muthuganapathy
(11)
,
Ganapathy Krishnamurthi
(11)
,
Andrew Jesson
(12)
,
Tal Arbel
(12)
,
Oskar Maier
(13)
,
Heinz Handels
(13)
,
Leonardo O. Iheme
(14)
,
Devrim Unay
(14)
,
Saurabh Jain
(15)
,
Diana M. Sima
(15)
,
Dirk Smeets
(15)
,
Mohsen Ghafoorian
(16)
,
Bram Platel
(17)
,
Ariel Birenbaum
(18)
,
Hayit Greenspan
(19)
,
Pierre-Louis Bazin
(20)
,
Peter A. Calabresi
(4)
,
Ciprian M. Crainiceanu
(21)
,
Lotta M. Ellingsen
(2, 22)
,
Daniel S. Reich
(4, 23)
,
Jerry L. Prince
(2)
,
Dzung L. Pham
(8)
1
Department of Computer Science [Baltimore]
2 ECE - Department of Electrical and Computer Engineering [Johns Hopkins University]
3 CNRM - Center for Neuroscience and Regenerative Medicine [Bethesda]
4 Department of Radiology and Radiological Science [Baltimore]
5 NMR Research Unit [London]
6 TIG - Translational imaging group [London]
7 DRC - Dementia Research Centre [London]
8 CNRM - Centre national de recherches météorologiques
9 VisAGeS - Vision, Action et Gestion d'informations en Santé
10 CRL - Computational Radiology Laboratory [Boston]
11 Department of Engineering Design [Madras]
12 CIM - Centre for Intelligent Machines
13 Institute of Medical Informatics [Lübeck]
14 Biomedical Engineering [Istanbul]
15 Icometrix [Leuven]
16 ICIS - Institute for Computing and Information Sciences [Nijmegen]
17 Diagnostic Image Analysis Group [Nijmegen]
18 Department of Electrical Engineering
19 TAU - Department of Biomedical Engineering [Tel Aviv]
20 Department of neurophysics [Leipzig]
21 Department of Biostatistics [Baltimore]
22 Department of electrical and computer engineering [Reykjavík]
23 Translational neuroradiology unit [Bethesda]
2 ECE - Department of Electrical and Computer Engineering [Johns Hopkins University]
3 CNRM - Center for Neuroscience and Regenerative Medicine [Bethesda]
4 Department of Radiology and Radiological Science [Baltimore]
5 NMR Research Unit [London]
6 TIG - Translational imaging group [London]
7 DRC - Dementia Research Centre [London]
8 CNRM - Centre national de recherches météorologiques
9 VisAGeS - Vision, Action et Gestion d'informations en Santé
10 CRL - Computational Radiology Laboratory [Boston]
11 Department of Engineering Design [Madras]
12 CIM - Centre for Intelligent Machines
13 Institute of Medical Informatics [Lübeck]
14 Biomedical Engineering [Istanbul]
15 Icometrix [Leuven]
16 ICIS - Institute for Computing and Information Sciences [Nijmegen]
17 Diagnostic Image Analysis Group [Nijmegen]
18 Department of Electrical Engineering
19 TAU - Department of Biomedical Engineering [Tel Aviv]
20 Department of neurophysics [Leipzig]
21 Department of Biostatistics [Baltimore]
22 Department of electrical and computer engineering [Reykjavík]
23 Translational neuroradiology unit [Bethesda]
Aaron Carass
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- Function : Correspondent author
- PersonId : 1008847
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Pierre Maurel
- Function : Author
- PersonId : 2625
- IdHAL : pierre-maurel
- ORCID : 0000-0003-2539-7414
- IdRef : 13063185X
Olivier Commowick
- Function : Author
- PersonId : 14904
- IdHAL : olivier-commowick
- ORCID : 0000-0001-7345-6752
- IdRef : 113377983
Christian Barillot
- Function : Author
- PersonId : 1245
- IdHAL : cbarillot
- ORCID : 0000-0002-1589-7696
- IdRef : 074123637
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.
Origin : Files produced by the author(s)
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