Replacing the humeral head with an artificial one via surgery is one of the options to treat glenohumeral osteoarthritis. Thus, designing the artificial humeral head is an important step to alter clinical outcomes. In order to design the artificial humeral head, the individual variety of the humeral heads should be investigated. The statistical shape model (SSM) has been attracting considerable attention to grasp 3-D shape variety; however, no method to derive the SSM of humeral heads has been studied. This paper proposes a method to construct an SSM of humeral heads based on the anatomical landmarks in shoulder computed tomography (CT) images. The proposed method consists of three steps: humeral head extraction, position and pose alignment, and finally, principle component analysis. The method was applied to 22 male subjects with leave-one-out cross validation. The proposed method obtained an average Dice coefficient of 0.92 to represent the individual shape using the constructed SSM. According to shape analysis of the humeral head, we found that the thickness of the humeral head was associated with individual characteristics of the humeral head. Therefore, it can be said that this study can provide patient-specific design of an artificial humeral head.

中文翻译：

---

CT图像中3-D肱骨头统计形状模型的构建

通过手术将肱骨头替换为人工肱骨头是治疗盂肱骨骨关节炎的一种选择。因此，设计人工肱骨头是改变临床结果的重要步骤。为了设计人工肱骨头，应该研究各个肱骨头的种类。统计形状模型（SSM）在吸引3D形状变化方面引起了极大的关注。但是，尚未研究得出肱骨头的SSM的方法。本文提出了一种基于肩部计算机断层扫描（CT）图像中的解剖标志构造肱骨头SSM的方法。所提出的方法包括三个步骤：肱骨头提取，位置和姿势对准以及最后的主成分分析。该方法已应用于22名留一法交叉验证的男性受试者。所提出的方法使用构造的SSM获得了0.92的平均Dice系数来表示单个形状。根据肱骨头的形状分析，我们发现肱骨头的厚度与肱骨头的个性有关。因此，可以说这项研究可以提供针对患者的人工肱骨头设计。