12种常用心脏MRI配准方法的DRAMMS验证。

Yangming Ou, Dong Hye Ye, Kilian M Pohl, Christos Davatzikos
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引用次数: 24

摘要

跨学科图像配准是许多心脏研究的基础。在文献中,它通常由体素级配准方法处理。然而,缺乏研究表明哪种方法在这种情况下更准确和稳定。针对这一问题,本文对12种流行的配准方法进行了评估,并在交叉学科心脏配准的背景下对最近发展起来的方法DRAMMS[16]进行了验证。我们的数据集包括24名受试者的短轴舒张末期心脏MR图像,其中非心脏结构被删除。每种配准方法应用于所有552对图像。通过源图像的变形专家标注与目标图像的相应专家标注之间的Jaccard重叠来逼近配准精度。该精度代理进一步与变形侵袭性相关,变形侵袭性通过雅可比行列式的最小值、最大值和范围反映出来。我们的研究表明,在该数据集中,DRAMMS[16]在准确性方面得分较高,并且很好地平衡了准确性和攻击性,其次是ANTs[13]、MI-FFD[14]、Demons[15]和ART[12]。我们在跨受试者心脏配准中的发现与脑图像配准的发现相呼应[7]。
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Validation of DRAMMS among 12 Popular Methods in Cross-Subject Cardiac MRI Registration.

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 [16] 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 [16] scores high in accuracy and well balances accuracy and aggressiveness in this dataset, followed by ANTs [13], MI-FFD [14], Demons [15], and ART [12]. Our findings in cross-subject cardiac registrations echo those findings in brain image registrations [7].

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