Orthopedic surgery is a branch of surgery concerned with treating the musculoskeletal system’s injuries and reconstruction. About half the population above the age of 50 suffer from some degree of osteoarthritis. According to the 2008 report of the American Academy of Orthopedic Surgery, the most common specialty among orthopedic practitioners (reporting more than one specialty) are adult knee (34%), arthroscopy (34%) sport and medicine (33%), total joint (28%), shoulder (25%) and adult hip (24%). Orthopedic surgeons practice an average of 32 orthopedic procedures per month. With growing population needs, a shortage of practitioners is expected in the next few years.
Hip replacement surgery measurements

Hip replacement surgery measurements

The work load can be reduced by introducing accurate efficient aid for each procedure, relieving the time burden in surgery planning and performance. Emerging technologies have completely altered the course of orthopedic surgery planning, simulation, and performance. Orthopedic surgeons can now benefit from the use of a mature set of computer vision tools for patient-specific measurement, navigation, surgical simulation, surface reconstruction, and implant design. Bringing point and surface registration in the field of orthopedics, computer vision and image processing hold the potential to improve surgical practices and affect surgery outcome to favor the benefit of patients and fast recovery.

The goal of these new technologies is to develop interactive patient-specific preoperative planners to optimize performance during surgery. Measurement accuracy being a strict constraint to computer-vision-based algorithms, as a matter of fact these algorithms are expected to operate for total knee replacement within less than 1 mm accuracy. Many registration algorithms have been proposed to meet the accuracy restriction for a given imaging modality (MRI, CT or ultrasound) and have been incorporated into routine surgery planning procedures. Fiducial points are either mechanically or optically marked to be able to deduce the rigid transformation needed for registration.

Measurement errors in finding fiducial points can be overcome via statistical means, by which the set of rigid transformations are estimated based on the most probable location of (ground-truth) fiducial markers. Once registration accuracy has been properly met, precise measurement can then follow by combination of image processing and mathematical modeling of the measured bone. For reconstruction purposes, like hip joint replacement, surgeons benefit from the accurate simulation of the functionality of a hip joint implant’s rotation and other degrees of freedom on the individual patient’s bone, e.g. over x-ray scan images.

Early registration systems in orthopedic implemented simple paired point matching. These algorithms relied on simple solution of a mathematical relationship between points but yielded insufficient accuracy. Coupled with surface matching, the accuracy of registration was improved. However, both techniques did not receive wide clinical acceptance. Other approaches include the calibration of (intraoperative) fluoroscopic and ultrasound images by feature and point intensity-based matching. Trade-off for registration should include, in addition for accuracy, the feasibility of acquiring landmark points for registration in a minimally invasive and radiation-free manner.

In total knee replacement, implant design needs to reach an alignment error of less than 3 degrees. These requirement have been empirically found to prevent long-term implant wear and allow more satisfactory function. Computer-based alignment systems now address these restriction by robust registration and accurate surface reconstruction. With advances in surface modeling and the ability to match a flexible surface model to observable fiducial points, reconstruction of an accurate surface for implant design is increasingly utilized in clinics.

Correct match between imaging modalities and the fabricated implant is crucial for the short and long-term success of orthopedic surgeries. With the increased incorporation of computer-vision and image processing techniques into the surgical planning and simulation process, the likelihood of success is on the rise. For these ends, computerized measurement tools have been constructed to perform crucial measurements. Semi or fully automated measurement tools have been constructed successfully by engineers of RSIP-Vision for over two decades. At RSIP Vision, we build computer-vision-based tools for measurement in semiconductors, tile industry and microscopy applications, always adhering to the strictest accuracy.

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