Audenaert E A, Van den Eynde J, de Almeida D F, Steenackers G, Vandermeulen D, Claes P
Department of Orthopedic Surgery and Traumatology, Ghent University Hospital, Corneel Heymanslaan 10, 9000 Ghent, Belgium.
Department of Human Structure and Repair, Ghent University, Corneel Heymanslaan 10, 9000 Ghent, Belgium.
Bone Rep. 2020 Jan 11;12:100243. doi: 10.1016/j.bonr.2020.100243. eCollection 2020 Jun.
Given sufficient training samples, statistical shape models can provide detailed population representations for use in anthropological and computational genetic studies, injury biomechanics, musculoskeletal disease models or implant design optimization. While the technique has become extremely popular for the description of isolated anatomical structures, it suffers from positional interference when applied to coupled or articulated input data. In the present manuscript we describe and validate a novel approach to extract positional noise from such coupled data. The technique was first validated and then implemented in a multicomponent model of the lower limb. The impact of noise on the model itself as well as on the description of sexual dimorphism was evaluated. The novelty of our methodology lies in the fact that no rigid transformations are calculated or imposed on the data by means of idealized joint definitions and by extension the models obtained from them.
在有足够训练样本的情况下，统计形状模型可为人类学和计算遗传学研究、损伤生物力学、肌肉骨骼疾病模型或植入物设计优化提供详细的群体表征。虽然该技术在描述孤立的解剖结构方面已变得极为流行，但在应用于耦合或关节连接的输入数据时会受到位置干扰。在本手稿中，我们描述并验证了一种从此类耦合数据中提取位置噪声的新方法。该技术首先经过验证，然后在下肢多组件模型中实现。评估了噪声对模型本身以及对性别二态性描述的影响。我们方法的新颖之处在于，不通过理想化的关节定义对数据计算或施加刚性变换，进而也不通过它们获得模型。
