Fast and Accurate DRRs for X-Ray Based Joint Surgery Planning


Currently available planning systems for joint replacement, are often based on two-dimensional (2D) X-rays and only focus on the determination of the likely size of the prosthesis that could fit the patient’s anatomy. Patient-specific biomechanical parameters in such systems are usually neglected as they are difficult to deduce from 2D X-ray images. However, functional and biomechanical information helps to optimize surgical procedures and thus achieve a compromise between balanced joint loading and joint stability to restore optimal dynamic joint function and longevity. The key challenge lies in the estimation of the three-dimensional (3D) geometry of the patient’s anatomy from clinically available X-rays alone. Methods relying on statistical shape models have been shown to be a promising avenue to solve this problem (Dworzak et al. IJCARS 5(2),2010). In such a scenario, the 3D shape to be reconstructed from the X-ray is parameterized via statistical analysis on a suitable training set (so called statistical shape model or SSM). The optimal parameters are determined via a minimization process, in which the SSM is repeatedly projected to the X-ray plane and the deviation of this projection from the X-ray is quantified.Up to now, most objective functions measure deviations between boundary features (Baka et al., MedIA 16(6) 2011) of the projected model and the structure in the X-ray (e.g. silhouettes).This has the drawback of requiring a careful segmentation of the structure in the X-ray. We are extending the previous approach by using 3D volumetric shape models, instead of surface models, in combination with intensity models (e.g. averaged radio-opacity or -translucency) defined on the whole volume of the shape (SSIM).This allows for a direct comparison ofthe “deformed” model X-rays with the patient X-ray in the optimization process -without accurate prior segmentation.For efficient optimization an accurate and fast projection algorithm is crucial, since the objective function shall model a good match and will be evaluated many times. Here, we present a hardware accelerated method for SSIM projection.

Proc. Int. Society of Computer Assisted Orthopaedic Surgery (CAOS), no. 293, 2012
Hans Lamecker
Hans Lamecker
Managing Director

Advancing 3D analysis, planning, design and manufacturing using innovative computational methods and tools