Ferretti Roberta, Dellepiane Silvana G
DITEN, Università degli Studi di Genova, Via Opera Pia 11a, 16145 Genova, Italy.
Int J Biomed Imaging. 2017;2017:7232751. doi: 10.1155/2017/7232751. Epub 2017 Oct 19.
This paper describes a method based on an automatic segmentation process to coregister carpal bones of the same patient imaged at different time points. A rigid registration was chosen to avoid artificial bone deformations and to allow finding eventual differences in the bone shape due to erosion, disease regression, or other eventual pathological signs. The actual registration step is performed on the basis of principal inertial axes of each carpal bone volume, as estimated from the inertia matrix. In contrast to already published approaches, the proposed method suggests splitting the 3D rotation into successive rotations about one axis at a time (the so-called basic or elemental rotations). In such a way, singularity and ambiguity drawbacks affecting other classical methods, for instance, the Euler angles method, are addressed. The proposed method was quantitatively evaluated using a set of real magnetic resonance imaging (MRI) sequences acquired at two different times from healthy wrists and by choosing a direct volumetric comparison as a cost function. Both the segmentation and registration steps are not based on a priori models, and they are therefore able to obtain good results even in pathological cases, as proven by the visual evaluation of actual pathological cases.
本文描述了一种基于自动分割过程的方法,用于对同一患者在不同时间点成像的腕骨进行配准。选择刚性配准以避免人工骨变形,并允许发现由于侵蚀、疾病消退或其他最终病理迹象导致的骨形状的最终差异。实际的配准步骤是基于从惯性矩阵估计的每个腕骨体积的主惯性轴来执行的。与已发表的方法不同,所提出的方法建议将3D旋转分解为一次围绕一个轴的连续旋转(所谓的基本或元素旋转)。通过这种方式,解决了影响其他经典方法(例如欧拉角方法)的奇异性和模糊性缺点。使用从健康手腕在两个不同时间获取的一组真实磁共振成像(MRI)序列,并选择直接体积比较作为代价函数,对所提出的方法进行了定量评估。分割和配准步骤都不基于先验模型,因此即使在病理情况下也能够获得良好的结果,实际病理病例的视觉评估证明了这一点。