X-RAY FLUOROSCOPY SPATIOTEMPORAL FILTERING WITH OBJECT DETECTION

One potential way to reduce patient and staff xray fluoroscopy dose is to reduce the quantum exposure to the detector and compensate the add itional noise with digital filtering. A new filtering method, spatio-t emporal filtering with object detection, is described that reduces noi se while minimizing motion and spatial blur. As compared to some conve ntional motion-detection filtering schemes, this object-detection meth od incorporates additional a priori knowledge of image content; i.e. m uch of the motion occurs in isolated long thin objects (catheters, gui de wires, etc.). We create object-likelihood images and use these to c ontrol spatial and recursive temporal filtering such as to reduce blur ring the objects of interest. We use automatically computed receiver o perating characteristic (ROC) curves to optimize the object-likelihood enhancement method and determine that oriented matched filter kernels with 4 orientations are appropriate. The matched filter kernels are s imple projected cylinders. We demonstrate the method on several repres entative x-ray fluoroscopy sequences to which noise is added to simula te very low dose acquisitions. With processing, we find that noise var iance is significantly reduced with slightly less noise reduction near moving objects. We estimate an effective exposure reduction greater t han 80%.