Generalized overlap measures for evaluation and validation in medical image analysis
Generalized overlap measures for evaluation and validation in medical image analysis
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DOI：
10.1109/tmi.2006.880587
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发表时间：
2006-11-01
影响因子：
10.6
通讯作者：
Hill, Derek L. G.
中科院分区：
文献类型：
--
作者：
Crum, William R.;Camara, Oscar;Hill, Derek L. G.
图像的标记区域的重叠的措施，如骰子和谷本系数，已被广泛用于评估图像配准和分割算法。现代研究可以包括在多个图像上定义的多个标签，但大多数评估方案报告每个标记区域的一个重叠，简单地在多个图像上平均。在本文中，常见的重叠措施进行了推广，以衡量总重叠的标签集合定义在多个测试图像和帐户分数标签使用模糊集理论。该框架允许报告单个“品质因数”，其通过图像对、标签或整体来总结复杂实验的结果。定义了误差的互补度量，重叠距离，其捕获非重叠部分的空间范围，并且与在灰度图像上计算的Hausdorff距离相关。广义重叠措施的合成图像上的重叠，可以计算分析，并用作三维磁共振成像（MRI）脑图像的非刚性配准的相似性措施进行验证。最后，一个务实的分割地面真相是通过注册的磁共振图谱大脑20个单独的扫描，并与重叠的措施，以评估公开可用的大脑分割算法。
Measures of overlap of labelled regions of images, such as the Dice and Tanimoto coefficients, have been extensively used to evaluate image registration and segmentation algorithms. Modern studies can include multiple labels defined on multiple images yet most evaluation schemes report one overlap per labelled region, simply averaged over multiple images. In this paper, common overlap measures are generalized to measure the total overlap of ensembles of labels defined on multiple test images and account for fractional labels using fuzzy set theory. This framework allows a single "figure-of-merit" to be reported which summarises the results of a complex experiment by image pair, by label or overall. A complementary measure of error, the overlap distance, is defined which captures the spatial extent of the nonoverlapping part and is related to the Hausdorff distance computed on grey level images. The generalized overlap measures are validated on synthetic images for which the overlap can be computed analytically and used as similarity measures in nonrigid registration of three-dimensional magnetic resonance imaging (MRI) brain images. Finally, a pragmatic segmentation ground truth is constructed by registering a magnetic resonance atlas brain to 20 individual scans, and used with the overlap measures to evaluate publicly available brain segmentation algorithms.