Abstract
Assessment of x-ray angiography system performance is typically performed using stationary test objects with simple geometries such as a disk on a uniform background. However, these methods do not represent realistic imaging conditions in interventional cardiology as anatomy and devices are inherently non-stationary due to cardiac motion. In this work, a novel implementation of the channelized Hotelling observer (CHO) was used to assess the influence of motion blur on object detectability. A standard CHO model assumes imaging system stationarity whereby the detectability index of a test object is independent of location. However, real angiography systems are inherently non-stationary. While vendor correction gain factors and offset maps are used to compensate for visual non-uniformities, these corrections do not restore stationarity to the images. Methods to accommodate non-stationarity and allow assessment of the influence of motion blur on test object detectability will be presented. The effect of motion blur was quantified with the relative detectability index (), where the for an object when moving with constant linear velocity was compared to a low velocity ‘pseudo-stationary’ condition to account for system non-stationarity. The pseudo-stationary condition was used to isolate the influences of spatial non-stationarity and motion blur. Three different test object shapes (disks, spheres and capsules) with linear velocity in the range 0–30 cm · s−1 were tested. For 1 mm diameter objects and linear velocity 30 cm · s−1, was degraded by 37%, 33% and 42% for the disk, sphere and capsule respectively, relative to the pseudo-stationary condition. Considering all test objects with diameter greater than 2 mm and linear velocity 30 cm · s−1, was degraded by less than 10% due to motion. In summary, this work describes a new approach to assess performance of x-ray angiography systems using the CHO model and moving test objects.
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