Abstract
The intraoperative registration of preoperative CT volumes is a key process of most computer-assisted orthopedic surgery (CAOS) systems. In this work, is reported a new method for automatic registration of long bones, based on the segmentation of the bone cortical in intraoperative 3D ultrasound images. A bone classifier was developed based on features, obtained from the principal component analysis of the Hessian matrix, of every voxel in an intraoperative ultrasound volume. 3D freehand ultrasound was used for the acquisition of the intraoperative ultrasound volumes. Corresponding bone surface segmentations in ultrasound and preoperative CT imaging were used for the intraoperative registration. Validation on a phantom of the tibia produced encouraging results, with a maximum mean segmentation error of 0.34mm (SD=0.26mm) and a registration accuracy error of 0.64mm (SD=0.49mm).
Highlights
Zian Fanti,1 Fabian Torres,2 Eric Hazan-Lasri,3 Alfonso Gastelum-Strozzi,2 Leopoldo Ruiz-Huerta,2,4 Alberto Caballero-Ruiz,2,4 and F
Deep et al [4] reviewed the literature on computer-assisted orthopedic surgery (CAOS) for knee and hip arthroplasty; the authors conclude that CAOS systems have gained a pivotal role in lower limb arthroplasty. e use of image-guided surgery (IGS) systems in trauma has been explored for the last eight years approximately, and several methods and systems have been developed with various levels of success [5]
Results and Discussion e accuracy of the bone segmentation and registration was evaluated on a realistic phantom of the tibia, which was constructed with a synthetic tibial bone (ERP #1117-42, Sawbones Inc., Vashon, WA, USA) immersed in a hydrogel made of polyvinyl alcohol (PVA) diluted in 95% of water
Summary
Zian Fanti ,1 Fabian Torres ,2 Eric Hazan-Lasri, Alfonso Gastelum-Strozzi, Leopoldo Ruiz-Huerta, Alberto Caballero-Ruiz, and F. E main clinical applications of IGS systems in orthopedics are pedicle screw insertion, hip replacement, knee replacement, and fracture alignment [1]. E results showed that image-guided navigation allows for safe, effective, and accurate instrumentation of small ( ≤3 mm) to very small ( ≤2 mm) thoracic pedicles. E success of the surgery depends heavily on the skill and experience of the surgeon [6]; the use of CAOS systems in fracture fixation performed with arthroscopic procedures offers an improved visualization of the surgical site with position feedback [7]. It has been reported that the use of CAOS, in arthroscopic fracture reduction procedures, improves the accuracy of the Journal of Healthcare Engineering surgery and achieves a shorter and more effective patient recovery [8]. Intraoperative registration is a critical process of most CAOS systems, given that registration accuracy determines the precision of the surgical visualization, planning, and navigation with respect to the patient on the operating table [11]
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