Multi-rigid image segmentation and registration for the analysis of joint motion from three-dimensional magnetic resonance imaging.
Multi-rigid image segmentation and registration for the analysis of joint motion from three-dimensional magnetic resonance imaging.
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用于分析三维磁共振成像关节运动的多刚性图像分割和配准。
DOI：
10.1115/1.4005175
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发表时间：
2011
期刊：
影响因子：
--
通讯作者：
Haynor,David
中科院分区：
文献类型：
--
作者：
Hu,Yangqiu;Ledoux,WilliamR;Fassbind,Michael;Rohr,EricS;Sangeorzan,BruceJ;Haynor,David
我们报道了一种用于研究体内磁共振成像（MRI）扫描关节形态和运动学的图像分割和配准方法，并将其应用于足部和踝关节运动的分析。使用mri兼容的定位装置，在单个中性位置和其他七个位置（从足底最大屈曲、倒置和内旋到最大背屈、外翻和外旋）对一只脚进行扫描。提出了一种结合图割和水平集的分割方法。在随后的配准步骤中，通过将中立位置数据集与其他数据集注册，获得每个骨骼的单独刚体转换，从而产生它们之间运动的准确描述。该分割算法允许用户在不到30分钟（用户和计算机处理单元[CPU]）的总时间内交互式地描绘出中性位置体积中的14块脚骨。注册到其他7个位置需要大约10分钟的用户时间和5.25小时的CPU时间。为了验证我们的结果，将我们的结果与半自动分割程序3DViewnix的结果进行了比较。我们获得了非常好的一致性，除中间楔形骨和较小跖骨外，所有骨骼的体积重叠率均大于88%。中立位扫描与其他7个位置的配准，平均重叠率为94.25%，胫骨中立位与1号位置的最小重叠率为89.49%，可能是视场（FOV）不同造成的。为了在8个位置处理一只脚，我们的工具只需要最少的用户交互时间（总共不到30分钟），这一改进水平有可能使MRI的关节运动分析在研究和临床应用中实用。
We report an image segmentation and registration method for studying joint morphology and kinematics from in vivo magnetic resonance imaging (MRI) scans and its application to the analysis of foot and ankle joint motion. Using an MRI-compatible positioning device, a foot was scanned in a single neutral and seven other positions ranging from maximum plantar flexion, inversion, and internal rotation to maximum dorsiflexion, eversion, and external rotation. A segmentation method combining graph cuts and level set was developed. In the subsequent registration step, a separate rigid body transformation for each bone was obtained by registering the neutral position dataset to each of the other ones, which produced an accurate description of the motion between them. The segmentation algorithm allowed a user to interactively delineate 14 foot bones in the neutral position volume in less than 30 min total (user and computer processing unit [CPU]) time. Registration to the seven other positions took approximately 10 additional minutes of user time and 5.25 h of CPU time. For validation, our results were compared with those obtained from 3DViewnix, a semiautomatic segmentation program. We achieved excellent agreement, with volume overlap ratios greater than 88% for all bones excluding the intermediate cuneiform and the lesser metatarsals. For the registration of the neutral scan to the seven other positions, the average overlap ratio is 94.25%, while the minimum overlap ratio is 89.49% for the tibia between the neutral position and position 1, which might be due to different fields of view (FOV). To process a single foot in eight positions, our tool requires only minimal user interaction time (less than 30 min total), a level of improvement that has the potential to make joint motion analysis from MRI practical in research and clinical applications.