Difference between revisions of "MSChallenge"

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| ''MIAC''<br />S. Andermatt, J. Würfel, & P.C. Cattin<br />''' '''<br />
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| ''ATMS''<br />Olfa Ghribi<br /><br />
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| ''ATMS''<br />Olfa Ghribi<br /><br />
 
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| 89.844
 
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| 8
 
 
| ''Team VISAGES GCEM''<br />L. Catanese, O. Commowick, & C. Barillot<br />'''Automatic Graph Cut Segmentation of Multiple Sclerosis Lesions'''<br />{{pub|doi=10.1016/j.neuroimage.2016.12.064|pubmed=28087490|period=}}
 
| ''Team VISAGES GCEM''<br />L. Catanese, O. Commowick, & C. Barillot<br />'''Automatic Graph Cut Segmentation of Multiple Sclerosis Lesions'''<br />{{pub|doi=10.1016/j.neuroimage.2016.12.064|pubmed=28087490|period=}}
 
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| 9
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| 8
 
| ''Team IIT Madras''<br />S. Vaidya, A. Chunduru, R. Muthuganapathy, & G. Krishnamurthi<br />'''Longitudinal Multiple Sclerosis Lesion Segmentation using 3D Convolutional Neural Networks'''<br />{{pub|doi=10.1016/j.neuroimage.2016.12.064|pubmed=28087490|period=}}
 
| ''Team IIT Madras''<br />S. Vaidya, A. Chunduru, R. Muthuganapathy, & G. Krishnamurthi<br />'''Longitudinal Multiple Sclerosis Lesion Segmentation using 3D Convolutional Neural Networks'''<br />{{pub|doi=10.1016/j.neuroimage.2016.12.064|pubmed=28087490|period=}}
 
|
 
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| colspan="4" style="border-top:1px solid #87cefa;"|
 
| colspan="4" style="border-top:1px solid #87cefa;"|
 
|-
 
|-
| 10
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| 9
 
| ''Team MS*metrix*''<br />S. Jain, D.M. Sima, & D. Smeets<br />'''Automatic Longitudinal Multiple Sclerosis Lesion Segmentation'''<br />{{pub|doi=10.1016/j.neuroimage.2016.12.064|pubmed=28087490|period=}}
 
| ''Team MS*metrix*''<br />S. Jain, D.M. Sima, & D. Smeets<br />'''Automatic Longitudinal Multiple Sclerosis Lesion Segmentation'''<br />{{pub|doi=10.1016/j.neuroimage.2016.12.064|pubmed=28087490|period=}}
 
|
 
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| colspan="4" style="border-top:1px solid #87cefa;"|
 
| colspan="4" style="border-top:1px solid #87cefa;"|
 
|-
 
|-
| 11
+
| 10
 
| ''Lesion-TOADS''<br />N. Shiee, P.-L. Bazin, A. Ozturk, D. S. Reich, P. A. Calabresi, & D. L. Pham<br />'''A topology-preserving approach to the segmentation of brain images with multiple sclerosis lesions'''<br />{{pub|doi=10.1016/j.neuroimage.2009.09.005|pubmed=19766196|pmcid=2806481|period=}}
 
| ''Lesion-TOADS''<br />N. Shiee, P.-L. Bazin, A. Ozturk, D. S. Reich, P. A. Calabresi, & D. L. Pham<br />'''A topology-preserving approach to the segmentation of brain images with multiple sclerosis lesions'''<br />{{pub|doi=10.1016/j.neuroimage.2009.09.005|pubmed=19766196|pmcid=2806481|period=}}
 
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| colspan="4" style="border-top:1px solid #87cefa;"|
 
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|-
| 12
+
| 11
 
| ''Team CMIC''<br />F. Prados, M.J. Cardoso, N. Cawley, O. Ciccarelli, C.A.M. Wheeler-Kingshott, & S. Ourselin<br />'''Multi-Contrast PatchMatch Algorithm for Multiple Sclerosis Lesion Detection'''<br />{{pub|doi=10.1016/j.neuroimage.2016.12.064|pubmed=28087490|period=}}
 
| ''Team CMIC''<br />F. Prados, M.J. Cardoso, N. Cawley, O. Ciccarelli, C.A.M. Wheeler-Kingshott, & S. Ourselin<br />'''Multi-Contrast PatchMatch Algorithm for Multiple Sclerosis Lesion Detection'''<br />{{pub|doi=10.1016/j.neuroimage.2016.12.064|pubmed=28087490|period=}}
 
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| colspan="4" style="border-top:1px solid #87cefa;"|
 
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| 13
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| 12
 
| ''MORF''<br />A. Jog, A. Carass, D.L. Pham, & J.L. Prince<br />'''Multi-Output Random Forests for Lesion Segmentation in Multiple Sclerosis'''<br />{{pub|doi=10.1117/12.2082157|pubmed=27695155|pmcid=5041594|period=}}
 
| ''MORF''<br />A. Jog, A. Carass, D.L. Pham, & J.L. Prince<br />'''Multi-Output Random Forests for Lesion Segmentation in Multiple Sclerosis'''<br />{{pub|doi=10.1117/12.2082157|pubmed=27695155|pmcid=5041594|period=}}
 
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| 14
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| 13
 
| ''Team TIG-BF''<br />C.H. Sudre, M.J. Cardoso, & S. Ourselin<br />'''Model Selection Propagation for Application on Longitudinal MS Lesion Segmentation'''<br />{{pub|doi=10.1016/j.neuroimage.2016.12.064|pubmed=28087490|period=}}
 
| ''Team TIG-BF''<br />C.H. Sudre, M.J. Cardoso, & S. Ourselin<br />'''Model Selection Propagation for Application on Longitudinal MS Lesion Segmentation'''<br />{{pub|doi=10.1016/j.neuroimage.2016.12.064|pubmed=28087490|period=}}
 
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| ''Team CRL''<br />X. Tomas-Fernandez & S.K. Warfield<br />'''Model of Population and Subject (MOPS) Segmentation'''<br />{{pub|doi=10.1016/j.neuroimage.2016.12.064|pubmed=28087490|period=}}
 
| ''Team CRL''<br />X. Tomas-Fernandez & S.K. Warfield<br />'''Model of Population and Subject (MOPS) Segmentation'''<br />{{pub|doi=10.1016/j.neuroimage.2016.12.064|pubmed=28087490|period=}}
 
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| ''Team DIAG''<br />M. Ghafoorian & B. Platel<br />'''Convolution Neural Networks for MS Lesion Segmentation'''<br />{{pub|doi=10.1016/j.neuroimage.2016.12.064|pubmed=28087490|period=}}
 
| ''Team DIAG''<br />M. Ghafoorian & B. Platel<br />'''Convolution Neural Networks for MS Lesion Segmentation'''<br />{{pub|doi=10.1016/j.neuroimage.2016.12.064|pubmed=28087490|period=}}
 
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| ''Team TIG''<br />C.H. Sudre, M.J. Cardoso, & S. Ourselin<br />'''Model Selection Propagation for Application on Longitudinal MS Lesion Segmentation'''<br />{{pub|doi=10.1016/j.neuroimage.2016.12.064|pubmed=28087490|period=}}
 
| ''Team TIG''<br />C.H. Sudre, M.J. Cardoso, & S. Ourselin<br />'''Model Selection Propagation for Application on Longitudinal MS Lesion Segmentation'''<br />{{pub|doi=10.1016/j.neuroimage.2016.12.064|pubmed=28087490|period=}}
 
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| ''Team VISAGES DL''<br />H. Deshpande, P. Maurel, & C. Barillot<br />'''Sparse Representations and Dictionary Learning Based Longitudinal Segmentation of Multiple Sclerosis Lesions'''<br />{{pub|doi=10.1016/j.neuroimage.2016.12.064|pubmed=28087490|period=}}
 
| ''Team VISAGES DL''<br />H. Deshpande, P. Maurel, & C. Barillot<br />'''Sparse Representations and Dictionary Learning Based Longitudinal Segmentation of Multiple Sclerosis Lesions'''<br />{{pub|doi=10.1016/j.neuroimage.2016.12.064|pubmed=28087490|period=}}
 
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| 19
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| 18
 
| ''Team BAUMIP''<br />L.O. Iheme & D. Unay<br />'''Automatic White Matter Hyperintensity Segmentation using FLAIR MRI'''<br />{{pub|doi=10.1016/j.neuroimage.2016.12.064|pubmed=28087490|period=}}
 
| ''Team BAUMIP''<br />L.O. Iheme & D. Unay<br />'''Automatic White Matter Hyperintensity Segmentation using FLAIR MRI'''<br />{{pub|doi=10.1016/j.neuroimage.2016.12.064|pubmed=28087490|period=}}
 
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Revision as of 19:04, 31 January 2017

<meta name="title" content="The 2015 Longitudinal Multiple Sclerosis Lesion Segmentation Challenge" />

The 2015 Longitudinal MS Lesion Segmentation Challenge

2015 Longitudinal MS Lesion Segmentation Challenge
MS Challenge Overview MS Challenge Data MS Challenge Evaluation

I. Introduction

2015 Longitudinal Multiple Sclerosis Lesion Segmentation Challenge

The Longitudinal MS Lesion Segmentation Challenge was conducted at the 2015 International Symposium on Biomedical Imaging in New York, NY, April 16-19. Competing teams applied their automatic lesion segmentation algorithms to MR neuroimaging data acquired at multiple time points from MS patients. Algorithms were evaluated against manual segmentations from two raters in terms of their segmentation accuracy and ability to track lesion evolution.

34 Teams initially registered for the Challenge coming from 15 different countries, representing 27 different institutions/universities. Congratulations to Team IIT Madras (First Prize), Team PVG_1 (Second Prize), and Team IMI (Third Prize and Efficiency Prize)!

Information about the data is available here, and the evaluation software from here.


Current Leaderboard

A live leaderboard is maintained on the Smart Stats Website. This leaderboard is updated to include links to the associated papers; most currently point to the main Challenge Article: A. Carass, S. Roy, A. Jog, J.L. Cuzzocreo, E. Magrath, A. Gherman, J. Button, J. Nguyen, F. Prados, C.H. Sudre, M.J. Cardoso, N. Cawley, O. Ciccarelli, C.A.M. Wheeler-Kingshott, S. Ourselin, L. Catanese, H. Deshpande, P. Maurel, O. Commowick, C. Barillot, X. Tomas-Fernandez, S.K. Warfield, S. Vaidya, A. Chunduru, R. Muthuganapathy, G. Krishnamurthi, A. Jesson, T. Arbel, O. Maier, H. Handels, L.O. Iheme, D. Unay, S. Jain, D.M. Sima, D. Smeets, M. Ghafoorian, B. Platel, A. Birenbaum, H. Greenspan, P.-L. Bazin, P.A. Calabresi, C.M. Crainiceanu, L.M. Ellingsen, D.S. Reich, J.L. Prince, and D.L. Pham, "Longitudinal Multiple Sclerosis Lesion Segmentation: Resource and Challenge", NeuroImage, 148(C):77-102, 2017. (doi) (PubMed).

Leaderboard
Ranking   Method Name
Authors
Paper Title
Paper Link(s)
Website
Score
1 MV-CNN
A. Birenbaum & H. Greenspan
Multi-View Convolutional Neural Networks
91.267
2 MIAC
S. Andermatt, J. Würfel, & P.C. Cattin

91.011
3 Team PVG One
A. Jesson & T. Arbel
Hierarchical MRF and Random Forest Segmentation of MS Lesions and Healthy Tissues in Brain MRI
 (doi) (PubMed)
90.698
4 Team IMI
O. Maier & H. Handels
MS-Lesion Segmentation in MRI with Random Forests
 (doi) (PubMed)
90.283
5 ATMS
O. Ghribi

90.170
6 MV-CNN
A. Birenbaum & H. Greenspan
Multi-View Convolutional Neural Networks
 (doi)
90.070
7 Team VISAGES GCEM
L. Catanese, O. Commowick, & C. Barillot
Automatic Graph Cut Segmentation of Multiple Sclerosis Lesions
 (doi) (PubMed)
89.807
8 Team IIT Madras
S. Vaidya, A. Chunduru, R. Muthuganapathy, & G. Krishnamurthi
Longitudinal Multiple Sclerosis Lesion Segmentation using 3D Convolutional Neural Networks
 (doi) (PubMed)
89.159
9 Team MS*metrix*
S. Jain, D.M. Sima, & D. Smeets
Automatic Longitudinal Multiple Sclerosis Lesion Segmentation
 (doi) (PubMed)
88.744
10 Lesion-TOADS
N. Shiee, P.-L. Bazin, A. Ozturk, D. S. Reich, P. A. Calabresi, & D. L. Pham
A topology-preserving approach to the segmentation of brain images with multiple sclerosis lesions
 (doi) (PubMed) (PMCID 2806481)
88.465
11 Team CMIC
F. Prados, M.J. Cardoso, N. Cawley, O. Ciccarelli, C.A.M. Wheeler-Kingshott, & S. Ourselin
Multi-Contrast PatchMatch Algorithm for Multiple Sclerosis Lesion Detection
 (doi) (PubMed)
88.009
12 MORF
A. Jog, A. Carass, D.L. Pham, & J.L. Prince
Multi-Output Random Forests for Lesion Segmentation in Multiple Sclerosis
 (doi) (PubMed) (PMCID 5041594)
87.917
13 Team TIG-BF
C.H. Sudre, M.J. Cardoso, & S. Ourselin
Model Selection Propagation for Application on Longitudinal MS Lesion Segmentation
 (doi) (PubMed)
87.376
14 Team CRL
X. Tomas-Fernandez & S.K. Warfield
Model of Population and Subject (MOPS) Segmentation
 (doi) (PubMed)
87.017
15 Team DIAG
M. Ghafoorian & B. Platel
Convolution Neural Networks for MS Lesion Segmentation
 (doi) (PubMed)
86.916
16 Team TIG
C.H. Sudre, M.J. Cardoso, & S. Ourselin
Model Selection Propagation for Application on Longitudinal MS Lesion Segmentation
 (doi) (PubMed)
86.436
17 Team VISAGES DL
H. Deshpande, P. Maurel, & C. Barillot
Sparse Representations and Dictionary Learning Based Longitudinal Segmentation of Multiple Sclerosis Lesions
 (doi) (PubMed)
86.068
18 Team BAUMIP
L.O. Iheme & D. Unay
Automatic White Matter Hyperintensity Segmentation using FLAIR MRI
 (doi) (PubMed)
84.140


VII. Organizers

Primary Organizer:
Dzung Pham, Center for Neuroscience and Regenerative Medicine, Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD

Organizing committee members:
Pierre-Louis Bazin, Department of Neurophysics, Max Planck Institute, Leipzig, Germany
Aaron Carass, Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD
Peter Calabresi, Department of Neurology, Johns Hopkins University, Baltimore, MD
Ciprian Crainiceanu, Department of Biostatistics, Johns Hopkins University, Baltimore, MD
Lotta Ellingsen, Department of Electrical and Computer Engineering, University of Iceland, Reykjavik, Iceland
Qing He, Center for Neuroscience and Regenerative Medicine, Henry Jackson Foundation, Bethesda, MD
Jerry Prince, Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD
Daniel Reich, Translational Neuroradiology Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
Snehashis Roy, Center for Neuroscience and Regenerative Medicine, Henry Jackson Foundation, Bethesda, MD


VIII. Funding support

This challenge was supported in part by a grant from the National Institute of Neurological Disorders and Stroke (NINDS R01 NS070906). Funding for prizes was provided by the National Multiple Sclerosis Society.