Benchmark for Algorithms Segmenting the Left Atrium From 3D CT and MRI Datasets
Benchmark for Algorithms Segmenting the Left Atrium From 3D CT and MRI Datasets
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DOI：
10.1109/tmi.2015.2398818
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发表时间：
2015-07-01
影响因子：
10.6
通讯作者：
Rhode, Kawal S.
中科院分区：
文献类型：
--
作者：
Tobon-Gomez, Catalina;Geers, Arjan J.;Rhode, Kawal S.
了解左心房（LA）解剖结构对于房颤消融指导、纤维化量化和生物物理建模非常重要。从磁共振成像（MRI）和计算机断层扫描（CT）图像中分割LA是一个复杂的问题。这份手稿提出了一个基准，以评估算法，解决LA分割。数据集、地面实况和评价代码已通过http://www.cardiacatlas.org网站公开提供。该手稿还报告了在STACOM'13研讨会上与MICCAI'13一起进行的左心房分割挑战（LASC）的结果。向参与者提供了30个CT和30个MRI数据集进行分割。每名参与者对LA进行分段，包括LA附件主干的一小部分和肺静脉（PV）的近端部分。我们目前的结果为9算法的CT和8算法的MRI。结果表明，统计模型与区域增长方法相结合的方法是最适合处理拟议的任务。标准化地面实况和自动分割以减少不一致定义的区域的影响（例如，二尖瓣平面、肺静脉终点、左心耳）。这个标准化框架，这是这项工作的贡献，可用于标记和进一步分析解剖区域的LA。通过直接在左心房表面上执行标准化，我们可以处理多个输入数据，包括从不同电解剖标测系统导出的网格。
Knowledge of left atrial (LA) anatomy is important for atrial fibrillation ablation guidance, fibrosis quantification and biophysical modelling. Segmentation of the LA from Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) images is a complex problem. This manuscript presents a benchmark to evaluate algorithms that address LA segmentation. The datasets, ground truth and evaluation code have been made publicly available through the http://www.cardiacatlas.org website. This manuscript also reports the results of the Left Atrial Segmentation Challenge (LASC) carried out at the STACOM'13 workshop, in conjunction with MICCAI'13. Thirty CT and 30 MRI datasets were provided to participants for segmentation. Each participant segmented the LA including a short part of the LA appendage trunk and proximal sections of the pulmonary veins (PVs). We present results for nine algorithms for CT and eight algorithms for MRI. Results showed that methodologies combining statistical models with region growing approaches were the most appropriate to handle the proposed task. The ground truth and automatic segmentations were standardised to reduce the influence of inconsistently defined regions (e.g., mitral plane, PVs end points, LA appendage). This standardisation framework, which is a contribution of this work, can be used to label and further analyse anatomical regions of the LA. By performing the standardisation directly on the left atrial surface, we can process multiple input data, including meshes exported from different electroanatomical mapping systems.