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Validation of DRAMMS among 12 Popular Methods in Cross-Subject Cardiac MRI Registration

机译:验证跨对象心脏MRI注册中的12种流行方法中的DRAMM

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摘要

Cross-subject image registration is the building block for many cardiac studies. In the literature, it is often handled by voxel-wise registration methods. However, studies are lacking to show which methods are more accurate and stable in this context. Aiming at answering this question, this paper evaluates 12 popular registration methods and validates a recently developed method DRAMMS [] in the context of cross-subject cardiac registration. Our dataset consists of short-axis end-diastole cardiac MR images from 24 subjects, in which non-cardiac structures are removed. Each registration method was applied to all 552 image pairs. Registration accuracy is approximated by Jaccard overlap between deformed expert annotation of source image and the corresponding expert annotation of target image. This accuracy surrogate is further correlated with deformation aggressiveness, which is reflected by minimum, maximum and range of Jacobian determinants. Our study shows that DRAMMS [] scores high in accuracy and well balances accuracy and aggressiveness in this dataset, followed by ANTs [], MI-FFD [], Demons [], and ART []. Our findings in cross-subject cardiac registrations echo those findings in brain image registrations [].
机译:交叉对象的图像配准是许多心脏研究的构建块。在文献中,它通常由Voxel-Wise登记方法处理。然而,缺乏研究在这种情况下显示哪种方法更准确和稳定。旨在回答这个问题,本文评估了12个流行的注册方法,并验证了最近开发的方法DRAMMS []的交叉主体心脏登记。我们的数据集由来自24个受试者的短轴结束 - 舒张心脏图像组成,其中不存在非心脏结构。每个注册方法都应用于所有552个图像对。注册准确度近似通过Jaccard重叠之间的变形专家注释之间的源图像和目标图像的相应专家注释之间的重叠。这种准确性替代物与变形侵略性进一步相关,这反映了雅各的最小,最大和范围的雅各比的决定簇。我们的研究表明,在这个数据集中的准确性和良好的准确性和攻击性的准确性和攻击性很高,其次是蚂蚁[],MI-FFD [],Demons []和Art []。我们在跨对象心脏注册中的发现回应了脑图像注册中的那些结果[]。

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