Navigated Knee Surgery

In the human knee, there is a ligament attached at the femur and the tibia called the anterior cruciate ligament (ACL). The ACL provides stability in the knee joint. If a knee is moved beyond its natural range of motion the ACL can rupture and lead to an unstable knee joint motion. With a surgery treatment the ACL can be replaced with a graft. For the surgeon it is very demanding and it requires a lot of experience to see in arthroscopic images where the original ACL was attached and to place the graft at this exact location inside the knee joint. However, it is relatively simple to locate the placement of a drilling tunnel for the graft in a computer tomography (CT) or a magnetic resonance imaging (MRI) scan. In this thesis a navigation system for the localization of the tibial tunnel placement during an ACL reconstruction is implemented. With the navigation system it is possible to track the position of the camera and the position of the patient. These two positions and the located position of the drilling tunnel in a CT or MRI scan are used to calculate where the drilling tunnel should be in arthroscopic images. To find the exact position of the drilling tunnel in the image, some calibration steps are required. These calibration steps consist of the tool-tip calibration, the camera calibration, the hand-eye calibration and the patient referencing. To verify that a reasonable position in the arthroscopic images is shown the calibrations of the navigation system have been tested on its accuracy and different parameters are tried out. A deviation for the complete navigation system is determined too. In further projects the navigation system can be further developed and used to record arthroscopic images and corresponding pixel coordinates of the drilling tunnel placement. The next goal is a machine learning approach that could predict the placement at inference time without a navigation system