Motion detection in helical CT using data consistency conditions

In computed tomography (CT), unexpected motion can result in poor image quality after reconstruction. One way to detect this motion is to verify data consistency conditions (DCC). DCC are mathematical relationships that characterize the redundancy of the data and must be verified by the projections. Necessary conditions for cone-beam projections with a linear source trajectory state that the integral of the cosine weighted projections along each row of the detector must be equal. In this work, we apply these conditions to pairs of source positions along a helical trajectory by rebinning the projections to a virtual detector parallel to the line connecting the two source positions. Then, we construct a graph connecting source positions between which we can calculate DCC and we use the Dijkstra algorithm to compute the shortest path between the first source position and all the other ones. This method was tested on simulated projections of the dynamic version of the Forbild thorax phantom, mostly static at end-inhale except for one breathing cycle during the acquisition. The proposed method allows a clear identification of when motion occurs during the acquisition.