Comparison of algorithms for combining X-ray angiography images

Using a one-dimensional convective-dispersive model of contrast agent flow in a blood vessel, we optimized and compared algorithms for combining a temporal sequence of X-ray angiography images, each with incomplete arterial filling, into a single-output image with fully opacified arteries. The four algorithms were: maximum opacity (MO) with a maximum over time at each spatial location; matched filtering (MAT); recursive filtering (REC) with a maximum opacity; and an approximate matched filter (AMF) consisting of a correlation with a kernel that approximates the matched filter kernel followed by a maximum opacity operation. Based on the contrast-to-noise ratio (CNR), MAT is theoretically the best algorithm. However, with spatially varying clinical images, a poorly matched MAT kernel greatly degraded CNR to the point of even inverting artery contrast. The practical AMF method maintained uniform CNR values over the entire field of view and gave >90% of the theoretical limit set by MAT. REC and MO created fully opacified arteries, but provided little CNR enhancement. By holding CNR at a nominal reference value, simulations predicted that AMF could be used with a contrast agent volume reduced by as much as 66%. Alternatively, X-ray exposure rate could be lowered. Although MO and REC are more easily implemented, the contrast enhancement with AMF makes it attractive for processing diagnostic angiography images acquired with a reduced contrast agent dose.