Articular surface segmentation using active shape models for intraoperative implant assessment

Purpose In orthopedic surgeries, it is important to avoid intra-articular implant placements, which increase revision rates and the risk of arthritis. In order to support the intraoperative assessment and correction of surgical implants, we present an automatic detection approach using cone-beam computed tomography (CBCT). Methods Multiple active shape models (ASM) with specified articular surface regions are used to isolate the joint spaces. Fast and easy-to-implement methods are integrated in the ASM segmentation to optimize the robustness and accuracy for intraoperative application. A cylinder detection method is applied to determine metal implants. Intersections between articular surfaces and cylinders are detected and used to find intra-articular collisions. Results Segmentations of two calcaneal articular surfaces were evaluated on 50 patient images and have shown average surface distance errors of 0.59 and 0.46 mm, respectively. The proposed model-independent segmentation at the specified articular surface regions allowed to significantly decrease the error by 22 and 25