Correcting organ motion artifacts in x-ray CT medical imaging systems by adaptive processing. I. Theory

X-ray CT scanners provide images of transverse cross sections of the human body from a large number of projections. During the data acquisition process, which usually takes about 1 s, motion effects such as respiration, cardiac motion, and patient restlessness produce artifacts that appear as blurring, doubling, and distortion in the reconstructed images, and may lead to inaccurate diagnosis. To address this problem several processing techniques have been proposed that require a priori knowledge of the motion characteristics. This paper proposes a method, which makes no assumptions about the properties of the motion, to eliminate the motion artifacts. The approach in this paper uses a spatial overlap correlator scheme to accurately track organ motion in computed tomography imaging systems. Then, it is shown that as optimum processing scheme to remove organ motion effects is to apply adaptive interference cancellation (AIC) methods, which treat the output of the spatial overlap correlator as noise interference at the input of the AIC process. Furthermore, an AIC method does not require any kind of periodicity of the motion effects. Synthetic data tests demonstrate the validity of this approach and show that hardware modifications are essential for its implementation in x-ray CT medical imaging systems.