Multilevel algebraic reconstruction technique for x‐ray computed tomography

The performance of an iterative image reconstruction technique, the Algebraic Reconstruction Technique (ART), was improved to be basically a one‐iteration noniterative technique producing even better image quality for x‐ray CT. In this thesis, the factors affecting the performance of ART were first analyzed. Then a novel projection access order, the multilevel scheme (MLS) for ART was proposed. MLS is exactly the sequence of 1D FFT if the number of projections is a power of 2. Experimental tests using real CT data demonstrated that the new MLS‐ART technique outperforms the conventional Convolution Backprojection (CBP) method, by producing higher spatial resolution when the number of projections is taken satisfying the sampling criterion and smaller noise when the number of projections is relatively small. A computer simulation study which matches the real CT dosage and noise conditions further quantifies that MLS produces a larger MTF when the number of projections is taken above half of that required by the sampling criterion and a larger SNR when the number of projections is taken below that half. It also improves the performance of ART itself, in both the computational speed (by more than 10 times) and the physical image quality (both the high and low contrast detectabilities). This work provides a thorough physical comparison among different CT reconstruction techniques and it confirms that MLS ART will find applications in reconstructions of different CT models, especially in situations where the projection data are limited.