Edward Henry Chao

Novel approach to extend the scanner coverage beyond detector field-of-view

In oncology applications, images obtained from CT scanners are often used to estimate the radiation dose delivered to a target organ. Since the patient needs to be positioned in a similar manner as in a therapy machine, a part of the patient is often outside the FOV defined by the CT scanner. The patient anatomy outside FOV may lie in the treatment beam path and must be considered when calculating dose delivery. In addition, truncated projections often produce image artifacts and make attenuation estimation difficult. In this paper, we propose a reconstruction algorithm that allows adequate estimation of the object outside the FOV. We make use of the fact that the total attenuation of each ideal projection in a parallel sampling geometry remains constant over all views. To overcome the small fluctuation resulting from the non-perfect calibrations and patient motion, we use projections of two neighboring non-truncated views as the basis of the attenuation estimation. We use the magnitudes and slopes of the samples at the location of truncation to estimate the water cylinders that can best fit to the projection data outside the FOV. To improve the robustness of the algorithm, continuity constraints are placed on the fitting parameters. Extensive phantom and patient experiments were conducted to test the robustness and accuracy of the proposed algorithm. Results show that CT number accuracy is fully recovered inside the scan FOV. In all cases, the shape of the truncated object outside the FOV is recovered to an accuracy of a few millimeters.