Adaptive noise cancelling in computed tomography

The problem of image reconstruction from noisy projection data is considered. Adaptive noise canceling techniques are utilized to obtain noise-canceled projections in the data-preprocessing stage. Because noise encountered in computerized tomography is signal-dependent, an adaptive predictor is preferred to a fixed-parameter filter. Noise cancellation is achieved because the decorrelation time for broadband noise is less than that of narrowband signals. Both the tapped delay line structure and the lattice have been studied for implementing the adaptive linear predictor. The idea of forward-backward processing is used for circumventing the large error in the initial part of the noise-canceled projection data. The reconstruction is then completed from noise-filtered projection data using the convolution back projection method. Simulation results demonstrating the efficacy of the proposed method are presented