Recent years have seen exciting advances in Computer Assisted Surgery (CAS). CAS systems are currently in use which provide data to the surgeon, provide passive feedback and motion constraint, and even automate parts of the surgery by manipulating cutters and endoscopic cameras. For most of these systems, accurate registration between the patients anatomy and the CAS system is crucial: if the position of the surgical target is not knownwith sufficient accuracy, therapies cannot be applied precisely, and treatment efficacy falls. This thesis presents a system for recovering the position and orientation of the target anatomy in 3D space based on iterative comparison of 2D planar radiographs with preoperative CT data. More specifically, this system uses X-ray images acquired at the time of treatment, and iteratively compares them with synthetic images, known as Digitally Reconstructed Radiographs (DRRs), in order to estimate the position and orientation of the target anatomy. An intermediate data representation called a Transgraph is presented. The Transgraph is similar to the Lumigraph, or Light Field, and extends the computer graphics field called image-based rendering to transmission imaging. This representation speeds up computation of DRRs by over an order of magnitude compared to ray-casting techniques, without the use of special graphics hardware. A hardware based volume rendering technique is also presented. This approach is based on new texture mapping techniques which enable DRR generation using off the shelf consumer grade computer graphics hardware. These techniques permit computation of full resolution (512x512) DRRs based on 256x256x256 CT data in roughly 70ms. The registration system is evaluated for application to frameless stereotactic radiosurgery, and phantom studies are presented demonstrating accuracy comparable to current immobilization-based systems. Additional phantom studies are presented in which the registration system is used to measure implant orientation following total hip replacement surgery, improving on current practice by a more than factor of two.
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