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Image-guided radiotherapy using a three-dimensional (3D) camera as the on-board surface imaging system requires precise and accurate registration of the 3D surface images in the treatment machine coordinate system. Two simple calibration methods, an analytical solution as three-point matching and a least-squares estimation method as multipoint registration, were introduced to correlate the stereo-vision surface imaging frame with the machine coordinate system. Both types of calibrations utilized 3D surface images of a calibration template placed on the top of the treatment couch. Image transformational parameters were derived from corresponding 3D marked points on the surface images to their given coordinates in the treatment room coordinate system. Our experimental results demonstrated that both methods had provided the desired calibration accuracy of 0.5 mm. The multipoint registration method is more robust particularly for noisy 3D surface images. Both calibration methods have been used as our weekly QA tools for a 3D image-guided radiotherapy system.

Radiation oncology departments are becoming more complex in terms of documentation, calculation, and delivery of therapy. Automation of such processes minimizes the likelihood of human error in each, and is clearly the direction in which the discipline is heading. The patient treatment cycle should be seamlessly integrated; unfortunately this is seldom the case given the different systems involved. We describe the Emory University experience, with cautions provided based on our lessons learned.