15 March 2013 Pose estimation quality assessment for intra-operative image guidance systems
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Abstract
In trauma and orthopedic surgery screw assessment and trajectory prediction using two-dimensional X-ray images is very difficult due to projected 3D information. However screw assessment can be done with multiple X-ray images. If the X-ray image contains the projected implant geometry it can be used as global coordinate reference. Thereby multiple independent X-ray images can be synchronized by estimating the implant pose in each single image. Consequently high accuracy pose estimation is fundamental. To measure the outcome quality an evaluation process has been designed. The evaluation process investigates in its first step several clinical intra-operative anterior-posterior (AP) and medio-lateral (ML) X-ray images which have been analyzed using a manual pose estimation method. With the manual method the six 3D parameters of the implant pose are estimated. These parameters define as well the camera pose relative to the implant. Based on the pose parameters of all clinical cases the capturing range for typical AP and ML images is statistically defined. The implant was attached to a phantom with 16 steel balls which allows to calculate the ground truth pose. Afterwards several X-ray images of the phantom are taken within the statistically defined capturing range. With the known ground truth different pose estimation methods can be compared. For each method the estimation quality can be calculated. In addition this error calculation can be used to adjust the initial manually determined capturing range. This paper explains the error evaluation process and describes how to validate pose estimation methods for clinical applications.
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Adrian Egli, Adrian Egli, Gerhard Kleinszig, Gerhard Kleinszig, Adrian John, Adrian John, Alberto Fernandez, Alberto Fernandez, Juan Cardelino, Juan Cardelino, } "Pose estimation quality assessment for intra-operative image guidance systems", Proc. SPIE 8671, Medical Imaging 2013: Image-Guided Procedures, Robotic Interventions, and Modeling, 86711W (15 March 2013); doi: 10.1117/12.2007248; https://doi.org/10.1117/12.2007248
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