15 May 2003 Overcoming the distortion problem in image-enhanced fluoroscopy
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In this paper, we examine the problem of image distortion influoroscopy, in particular its effect applications in image-guided surgery that make use of tracking and calibration techniques to relate a point in physical space in the operating room (OR)to the corresponding pointin an intraoperative fluoroscopic image. We call such applications image-enhanced fluoroscopy. In order to derive the relationship between physical space and a fluoroscopic image, two sets of parameters must be known. The first set describes the pose of the fluoroscope at the time when the image was taken; these parameters are usually estimated by rigidly attaching a device to the fluoroscope that is able to be tracked by either an optical or magnetic tracking system present in the OR. The second set of parameters describes the projection model of the fluoroscope itself: this set includes focal length and X-ray source position relative to the image intensifier. In the case that we examine here, these values are estimated using a set of BBs of known geometry placed between the X-ray source and the image intensifier. Because the image intensifier is not perfectly planar, and also because of ambient magnetic fields, the image displayed by the fluoroscope does not match that predicted by a linear projection model. Using the known geometry of the BBs appearing in the image, we may attempt to recover the image that would be given by a linear projection. We call this process dewarping. In this paper, we address the question of the optimal dewarp function. Although a fifth-order polynomial is commonly used, we show that a third-order polynomial is superior. We use real fluoroscope images to demonstrate the potential dangers of using too high a polynomial order for the dewarping process.
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Jay B. West, Jay B. West, Rasool Khadem, Rasool Khadem, Calvin R. Maurer, Calvin R. Maurer, } "Overcoming the distortion problem in image-enhanced fluoroscopy", Proc. SPIE 5032, Medical Imaging 2003: Image Processing, (15 May 2003); doi: 10.1117/12.480845; https://doi.org/10.1117/12.480845

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