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SiSSR:用于犬类 CT 图像心功能定量分析的同时细分曲面配准。

SiSSR: Simultaneous subdivision surface registration for the quantification of cardiac function from computed tomography in canines.

机构信息

Institute of Biomedical Engineering, Department of Engineering, University of Oxford, United Kingdom; Department of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, USA; Tufts University School of Medicine, Sackler School of Graduate Biomedical Sciences, USA.

Department of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, USA.

出版信息

Med Image Anal. 2018 May;46:215-228. doi: 10.1016/j.media.2018.03.009. Epub 2018 Mar 29.

Abstract

Recent improvements in cardiac computed tomography (CCT) allow for whole-heart functional studies to be acquired at low radiation dose (<2mSv) and high-temporal resolution (<100ms) in a single heart beat. Although the extraction of regional functional information from these images is of great clinical interest, there is a paucity of research into the quantification of regional function from CCT, contrasting with the large body of work in echocardiography and cardiac MR. Here we present the Simultaneous Subdivision Surface Registration (SiSSR) method: a fast, semi-automated image analysis pipeline for quantifying regional function from contrast-enhanced CCT. For each of thirteen adult male canines, we construct an anatomical reference mesh representing the left ventricular (LV) endocardium, obviating the need for a template mesh to be manually sculpted and initialized. We treat this generated mesh as a Loop subdivision surface, and adapt a technique previously described in the context of 3-D echocardiography to register these surfaces to the endocardium efficiently across all cardiac frames simultaneously. Although previous work performs the registration at a single resolution, we observe that subdivision surfaces naturally suggest a multiresolution approach, leading to faster convergence and avoiding local minima. We additionally make two notable changes to the cost function of the optimization, explicitly encouraging plausible biological motion and high mesh quality. Finally, we calculate an accepted functional metric for CCT from the registered surfaces, and compare our results to an alternate state-of-the-art CCT method.

摘要

最近,心脏计算机断层扫描(CCT)技术的改进使得在单次心跳中以低辐射剂量(<2mSv)和高时间分辨率(<100ms)获取全心功能研究成为可能。尽管从这些图像中提取区域性功能信息具有重要的临床意义,但与超声心动图和心脏磁共振成像领域的大量工作相比,对 CCT 进行区域性功能定量的研究相对较少。在这里,我们提出了同时细分曲面配准(SiSSR)方法:一种用于从对比增强 CCT 中定量区域性功能的快速、半自动图像分析流水线。对于每只 13 只成年雄性犬,我们构建了一个代表左心室(LV)心内膜的解剖参考网格,避免了需要手动雕刻和初始化模板网格的问题。我们将生成的网格视为 Loop 细分曲面,并采用先前在 3-D 超声心动图背景下描述的技术,同时有效地将这些曲面注册到所有心脏帧的心内膜上。尽管之前的工作在单个分辨率下执行配准,但我们观察到细分曲面自然提出了一种多分辨率方法,从而导致更快的收敛并避免局部最小值。我们还对优化的代价函数进行了两项值得注意的更改,明确鼓励合理的生物学运动和高质量的网格。最后,我们从注册的曲面计算 CCT 的公认功能指标,并将我们的结果与替代的最先进的 CCT 方法进行比较。

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