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Updated: Aug 23, 2026

X-ray Dose Reduction through Adaptive Exposure in Fluoroscopic Imaging
Published on: September 11, 2011
Processing X-ray images to eliminate irrelevant structures that mask important features
1Department of Physiology and Biophysics, Georgetown University Medical Center, Washington DC, 20007, USA.
Abstract:
In a plane radiographic image, there generally is an important area of interest (AOI). Too often, the AOI is partially masked by images of other overlapping and underlying structures that may be in front of or behind the AOI. An important adjunct to radiological diagnosis would be the capability of eliminating images of such masking structures to isolate the AOI for more detailed examination. We described a computerized method that utilizes a stereo pair of plane X-ray images to enable radiologists to interact with these images for first identifying for the computer the AOI and then directing the computer to eliminate all structures in front of and behind the AOI. The result is a plane X-ray image or a stereo X-ray image pair that includes only the AOI, but not any overlapping or underlying structures. The method uses a stereo pair of X-rays and the 3D perception of radiologists. 3D perception involves eye convergence and lens focus as well as cues, such as parallax and relative sizes. Convergence of the eyes is by far the strongest factor in 3D visualization. The horizontal separation or disparity between points in the left and right eye images on a screen or X-ray film produces convergence which determines an object's perceived depth in visual 3D space. All points in a given perceived depth plane have the same disparity on the screen. In theory, a given depth plane can be eliminated from the 3D image by shifting one image and then the other image of a stereo pair horizontally by the distance of the disparity of the depth plane, and subtracting. A new stereo image pair is thereby produced in which points only of the depth plane do not appear. However, in practical situations, certain artifacts arise that must be considered. The method has the potential for important applications in many areas of medical imaging processing.
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