Determining 3D scapular orientation with scapula models and biplane 2D images. (March 2017)

• Record Type: Journal Article
• Authors: Nicholson, Kristen F; Richardson, R Tyler; Miller, Freeman; Richards, James G
• Is Part Of: Medical engineering & physics. Volume 41(2017)
• Page Start: 103
• Page End: 108
• Publication Date: 2017-03
• Subjects: Shoulder mechanics -- Image processing -- Model registration -- Biplane X-ray -- Biomechanics; ST scapulothoracic -- DRR digitally reconstructed radiographs -- TS trigonum spinae -- IA inferior angle -- AP acromion process; Biomedical engineering -- Periodicals; Biomedical Engineering -- Periodicals; Physics -- Periodicals; Génie biomédical -- Périodiques; Biomedical engineering; Electronic journals; Periodicals; 610.28
• DOI: 10.1016/j.medengphy.2017.01.012
• Languages: English
• ISSNs: 1350-4533

Abstract

Highlights: Accurate scapula orientation is important for understanding shoulder function. A 3D to 2D matching strategy was used to determine scapula orientation. Matched orientations compared favorably to motion capture orientations. The strategy was accurate for both subject specific models and general models. Abstract: This study evaluated a strategy for identifying 3D scapulothoracic orientation using bilateral X-ray scans and 3D scapula models. Both subject-specific scapula models and a scaled general model were utilized. 3D scapulothoracic orientations obtained from X-rays were compared to motion capture data. "Subjects" consisted of a skeletal model of a human torso and ten real bone scapulae. Retroreflective markers were placed on the scapulae and a three-marker triad was placed on the trunk. Marker positions were recorded using an eight camera motion capture system. A biplane X-ray system from EOS Imaging was used to collect two orthogonal 2D images of the skeleton and markers. Custom software was created for the 3D to 2D matching process. The results indicated that the matched orientations compared favorably to motion capture orientations, with RMSE errors ranging from 3.1° to 5.5° and a mean error of 3.9° The proposed strategy was shown to be accurate for both subject-specific models and a scaled general model.