Reconstruction from truncated projections in CT using adaptive detruncation.

If the object exceeds the field of measurement (FOM) of a given CT scanner, severe artifacts may result. In this work, we propose an adaptive detruncation (ADT) method to reconstruct images from medical CT projections which are truncated in the transaxial direction. The truncated projections are extrapolated by estimating the convex hull of the patient. The ADT method allows us not only to achieve artifact-free images in the FOM but also to extend the images beyond the FOM, and can therefore be very attractive, for example, in PET/CT scanners for attenuation correction.

Spiral scan long object reconstruction through PI line reconstruction.

The response of a point object in a cone beam (CB) spiral scan is analysed. Based on the result, a reconstruction algorithm for long object imaging in spiral scan cone beam CT is developed. A region-of-interest (ROI) of the long object is scanned with a detector smaller than the ROI, and a portion of it can be reconstructed without contamination from overlaying materials. The top and bottom surfaces of the ROI are defined by two sets of PI lines near the two ends of the spiral path. With this novel definition of the top and bottom ROI surfaces and through the use of projective geometry, it is straightforward to partition the cone beam image into regions corresponding to projections of the ROI, the overlaying objects or both. This also simplifies computation at source positions near the spiral ends, and makes it possible to reduce radiation exposure near the spiral ends substantially through simple hardware collimation. Simulation results to validate the algorithm are presented.

Filtering point spread function in backprojection cone-beam CT and its applications in long object imaging.

In backprojection cone-beam CT the cone-beam projection images are first filtered, then 3D backprojected into the object space. In this paper the point spread function (PSF) for the filtering operation is studied. For the cases where the normalization matrix is a constant, i.e. all integration planes intersect the scan path the same number of times, the derivation of the PSF is extended to the general case of limited angular range for the Radon line integrals. It is found that the 2D component of the PSF can be reduced to the form of space-variant 1D Hilbert transforms. The application of the PSF to a number of aspects in long object imaging will be discussed.

Exact (spiral + circles) scan region-of-interest cone beam reconstruction via backprojection.

We present a (spiral + circles) scan cone beam reconstruction algorithm in which image reconstruction proceeds via backprojection in the object space. In principle, the algorithm can reconstruct sectional region-of-interest (ROI) in a long object. The approach is a generalization of the cone beam backprojection technique developed by Kudo and Saito in two aspects: the resource-demanding normalization step in the Kudo and Saito's algorithm is eliminated through the technique of data combination that we published earlier, and the elimination of the restriction that the detector be big enough to capture the entire cone beam projection of the ROI. Restricting the projection data to the appropriate angular range required by data combination can be accomplished by a masking process. Because of the simplification resulting from the elimination of the normalization step, the most time-consuming operations of the algorithm can be approximated by the efficient step of line-by-line ramp filtering the cone beam image in the direction of the scan path, plus a correction image. The correction image, which can be computed exactly, is needed because data combination is not properly matched at the mask boundary when ramp filtering is involved. Empirical two-dimensional (2-D) point spread function (PSF) is developed to improve matching with the correction image which is computed with finite samplings. The use of transition region to further improve matching is introduced. The results of testing the algorithm on simulated phantoms are presented.