The present invention relates to x-ray fluoroscopy systems and, more particularly, to a method and apparatus for performing an adaptive fluoroscopic noise reduction algorithm on image data acquired by an x-ray fluoroscopy system.
In x-ray fluoroscopy systems, a process known as fluoroscopic noise reduction (FNR) is performed on image frames acquired by a fluoroscopic x-ray detector of the x-ray fluoroscopy system. The objective of the FNR process is to filter noise out of the image data while preserving contrast information in the image data. To accomplish this, temporal filtering is performed on areas in the image where there is no motion. In areas in the image where there is motion, no filtering is performed.
FNR is typically performed by temporally averaging image frames in regions where there is no motion. Pixel-by-pixel motion detection is utilized to determine the existence or absence of motion in the image data from frame to frame. Therefore, pixel-by-pixel motion detection is one of the most critical stages in the FNR process because the accuracy of the motion detection affects the preservation of contrast of moving objects within the image, such as, for example, guidewires or stents.
Current FNR techniques rely on defining global limits for motion detection and these limits are applicable to the entire image. These limits affect the strength and extent of temporal averaging performed on the image data. One disadvantage of the current FNR techniques is that the global limits, which are defined a priori, are set for the entire image and do not take into account the non-stationary nature of image statistics in space. Furthermore, the global limits do not take into account the fact that object contrast and noise are functions of the exposure management (EM) trajectory parameters and other acquisition parameters of the x-ray fluoroscopy system.
Noise statistics vary as a function of mean photons in the detector elements of the x-ray fluoroscopic detector which, in turn, depends on background, the object being imaged and the EM trajectory being used. Also, the panel parameters of the x-ray fluoroscopy system play an important role in converting photon quantum noise into a digital signal for a given EM trajectory. It would be desirable to provide an x-ray fluoroscopy system that takes into account noise statistics, object contrast and other system parameters in performing motion detection and in determining the extent of temporal filtering to be performed on the image data.
Accordingly, a need exists for a method and apparatus for performing fluoroscopic noise reduction which utilize noise statistics, object contrast and other system parameters in determining which regions in an image are to be temporally filtered and, if so, the extent of the temporal filtering performed.