3-D Statistical Shape Model of the Humerus Towards Artificial Shoulder Joint Design

Kubo, Yuki; Hossain, Belayat; Nii, Manabu; Muto, Tomoyuki; Tanaka, Hiroshi; Inui, Haruyuki; Nobuhara, Katsuya; Kobashi, Syoji

doi:10.23919/wac.2018.8430413

Cited by 1 publication

(3 citation statements)

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“…The shape parameter of the test data was calculated by An SSM can express the interindividual variation of the shape by the mean (i.e., average shape), the eigenvectors, and the PC scores (i.e., shape parameter). It can also reconstruct the original individual shape [5]. The shape of one subject was chosen as the test data, whereas the shapes of all other subjects were used to build an SSM.…”

Section: Construction Of Humeral Head Ssm and Its Performance Evaluationmentioning

confidence: 99%

“…Research studies showed that artificial humeral head design with some kind approximation (e.g., spherical or elliptical) did not bring an adequate outcome [4]. It also limited the range of motion (ROM) of the shoulder [5]. Some studies showed that increasing the similarity between the artificial humeral head and the actual one could increase the ROM of the shoulder [4,6].…”

Section: Introductionmentioning

confidence: 99%

“…The proposed method consists of three steps: segmentation of humerus, humeral head extraction, pose alignment of humeral head, and finally, construction of the SSM by applying PCA. This study particularly focuses on the shape of the humeral head, whereas our previous study [5] focused on the shape of the whole humerus. Furthermore, this experiment demonstrates the effectiveness of SSMs by studying the individual shape variability using the SSM.…”

Section: Introductionmentioning

confidence: 99%

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Construction of 3-D Humeral Head Statistical Shape Model in CT Images

et al. 2020

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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.

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Section: Construction Of Humeral Head Ssm and Its Performance Evaluationmentioning

confidence: 99%