Regression forest-based automatic estimation of the articular margin plane for shoulder prosthesis planning.
作者： Michael Tschannen , Lazaros Vlachopoulos , Christian Gerber , Gábor Székely , Philipp Fürnstahl
DOI: 10.1016/J.MEDIA.2016.02.008
关键词:
摘要: In shoulder arthroplasty, the proximal humeral head is resected by sawing along cartilage-bone transition and replaced a prosthetic implant. The resection plane, called articular margin plane (AMP), defines orientation, position size of in relation to shaft. Therefore, correct definition AMP crucial for computer-assisted preoperative planning arthroplasty. We present fully automated method estimating relying only on computed tomography (CT) images upper arm. It consists two consecutive steps, each which uses random regression forests (RFs) establish direct mapping from CT image parameters. first step, intensities serve as features compute coarse estimate AMP. second step builds upon this estimate, calculating refined using novel feature types that combine bone enhancing sheetness measure with ray features. proposed was evaluated dataset consisting 72 arm cadavers. A mean localization error 2.40mm angular 6.51° measured compared manually annotated ground truth.
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