ESTIMATING THE 2-DIMENSIONAL BLOOD-FLOW VELOCITY MAP FROM CINEANGIOGRAMS - ALGORITHM USING AN INITIAL GUESS AND ITS APPLICATION TO AN ABDOMINAL ANEURYSM

To derive blood flow dynamics from cineangiograms (CAG), we have devel oped an image processing algorithm to estimate a two-dimensional blood flow velocity map projected on CAG. Each image area of CAG is divided into blocks, and it is assumed that the movement of the contrast medi um between two serial frames is restricted only to adjacent blocks. By this assumption, a ''fundamental equation'' and the ''maximum flow co nstraints'' are derived. The equation and constraints state the relati onship between the volume of contrast medium in each block and the ''f low components'' that are the volumes of contrast medium flowing from/ to its adjacent blocks. The ''initial guess'' that is a set of approxi mately obtained flow components is corrected using these relationships . The corrected flow components are then transformed into blood flow v elocities, which are illustrated in the form of a needle diagram. In n umerical experiments, the estimation error between the real flow veloc ity generated artificially and the flow velocity estimated with our al gorithm was evaluated under one of the worst conditions. Although the maximum error was fairly large, the estimated flow velocity map was st ill acceptable for visual inspection of flow velocity pattern. We then applied our algorithm to an abdominal CAG (clinical data). The result s showed flow stagnation and reverse flow in the abdominal aneurysm, w hich are consistent with the presence of a thrombus in the aneurysm. T his algorithm may be a useful diagnostic tool in the assessment of vas cular disease.