Registration-based segmentation of murine 4D cardiac micro-CT data using symmetric normalization
Registration-based segmentation of murine 4D cardiac micro-CT data using symmetric normalization
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DOI：
10.1088/0031-9155/57/19/6125
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发表时间：
2012-10-07
影响因子：
3.5
通讯作者：
Badea, Cristian T.
中科院分区：
文献类型：
--
作者：
Clark, Darin;Badea, Alexandra;Badea, Cristian T.
微型CT具有较高的空间和时间分辨率，可在心血管疾病的临床前研究中发挥重要作用。4D心脏图像的定量分析需要在每个时间点分割心腔，如果手动完成，这是一个非常耗时的过程。为了提高吞吐量，本研究提出了一种基于配准的分割和功能分析的4D心脏micro-CT数据在小鼠中的管道。在使用模拟进行优化和验证之后，将流水线应用于对应于在C57 BL/6小鼠（n = 5）中采集的十个心脏相位的体内心脏微CT数据。在采用新型4D双边滤波适应进行边缘保留平滑后，手动分割每个心脏序列中的一个相位。可变形配准用于将这些标签传播到所有其他心脏相位以进行分割。计算每个心腔的容积，并用于推导每搏输出量、射血分数、心输出量和心脏指数。骰子系数和体积精度被用来比较手动分割的两个额外的阶段与其相应的传播标签。平均而言，左心室的两个测量值均>0.90，心肌、右心室和右心房的测量值均>0.80，这与节段间和节段内变异性的趋势一致。左心房的分割不太可靠。平均而言，由于房室瓣周围的系统性标签传播错误，感兴趣的功能指标被低估了6.76%或更多;然而，管道的执行比执行每个阶段的类似手动分割快80%。
Micro-CT can play an important role in preclinical studies of cardiovascular disease because of its high spatial and temporal resolution. Quantitative analysis of 4D cardiac images requires segmentation of the cardiac chambers at each time point, an extremely time consuming process if done manually. To improve throughput this study proposes a pipeline for registration-based segmentation and functional analysis of 4D cardiac micro-CT data in the mouse. Following optimization and validation using simulations, the pipeline was applied to in vivo cardiac micro-CT data corresponding to ten cardiac phases acquired in C57BL/6 mice (n = 5). After edge-preserving smoothing with a novel adaptation of 4D bilateral filtration, one phase within each cardiac sequence was manually segmented. Deformable registration was used to propagate these labels to all other cardiac phases for segmentation. The volumes of each cardiac chamber were calculated and used to derive stroke volume, ejection fraction, cardiac output, and cardiac index. Dice coefficients and volume accuracies were used to compare manual segmentations of two additional phases with their corresponding propagated labels. Both measures were, on average, >0.90 for the left ventricle and >0.80 for the myocardium, the right ventricle, and the right atrium, consistent with trends in inter- and intra-segmenter variability. Segmentation of the left atrium was less reliable. On average, the functional metrics of interest were underestimated by 6.76% or more due to systematic label propagation errors around atrioventricular valves; however, execution of the pipeline was 80% faster than performing analogous manual segmentation of each phase.