Longitudinal multiple sclerosis lesion segmentation: Resource and challenge.
Longitudinal multiple sclerosis lesion segmentation: Resource and challenge.
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DOI：
10.1016/j.neuroimage.2016.12.064
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发表时间：
2017-03-01
期刊：
影响因子：
5.7
通讯作者：
Pham DL
中科院分区：
文献类型：
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作者：
Carass A;Roy S;Jog A;Cuzzocreo JL;Magrath E;Gherman A;Button J;Nguyen J;Prados F;Sudre CH;Jorge Cardoso M;Cawley N;Ciccarelli O;Wheeler-Kingshott CAM;Ourselin S;Catanese L;Deshpande H;Maurel P;Commowick O;Barillot C;Tomas-Fernandez X;Warfield SK;Vaidya S;Chunduru A;Muthuganapathy R;Krishnamurthi G;Jesson A;Arbel T;Maier O;Handels H;Iheme LO;Unay D;Jain S;Sima DM;Smeets D;Ghafoorian M;Platel B;Birenbaum A;Greenspan H;Bazin PL;Calabresi PA;Crainiceanu CM;Ellingsen LM;Reich DS;Prince JL;Pham DL
结合 ISBI 2015 会议，我们组织了纵向病变分割挑战赛，为注册参与者提供培训和测试数据。训练数据包括 5 名受试者，平均 4.4 个时间点，测试数据包括 14 名受试者，平均 4.4 个时间点。所有 82 个数据集都有由两名人类专家评估者描绘的与多发性硬化症相关的白质病变。十一个团队使用最先进的病变分割算法提交了挑战结果，其中十个团队在会议上展示了他们的结果。我们提出了定量评估，比较了两个评估者的一致性，并探索了十一个提交结果以及其他三个病变分割算法的性能。该挑战带来了三个独特的机会：1）共享丰富的数据集； 2) 社区中正在进行的各种研究途径的协作和比较； 3) 对当前使用的评估指标进行审查和完善。我们报告挑战参与者的表现，以及共识划分的构建和评估。图像数据和手册描述将继续通过评估网站1提供下载，作为该领域未来研究人员的资源。该数据资源提供了一个平台，可以以公平一致的方式相互比较现有方法以及多个手动评估者。
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 website1 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.