Reconstruction of blood vessels from x-ray subtraction projections: Limited angle geometry

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Abstract
Several algorithms have been investigated for reconstructing blood vessels from a limited number of x-ray subtraction projections, distributed over a limited range of angles. Both computer simulations and an in vivo animal study were carried out. The best reconstruction performance was achieved using an algorithm that folded in two pieces of a priori knowledge of the vascular density distributions: (1) the object is dilute, consisting mainly of a void; and (2) the density distribution in the reconstructions is most likely to be non-negative. Both the signal-to-noise ratio (SNR) and the signal to out-of-focus blur were quantitated. Compared to tomosynthetic reconstruction (backprojection), the amount of residual blur from out-of-focus planes was significantly reduced with only a small penalty in diminished SNR. The combined effect resulted in significant qualitative image improvement for real arterial distributions as demonstrated in a canine arterial imaging example.