CT imaging with truncated data over limited-angular ranges

Abstract

In certain CT applications such as dental CT imaging, a scanning configuration with an offset-detector is often used for extending the field of view (FOV) of the system. While data are truncated on one-side of the detector, it remains possible to accurately reconstruct an image from the truncated data collected over a full-angular range (FAR) of 360° by use of existing analytical-based algorithms such as the FDK algorithm. However, there also exist interests in scanning configurations that collect data only over limited-angular ranges (LARs) for practical considerations, and existing algorithms generally yield reconstructions with significant artifacts from LAR data collected with an offset-detector. It has been demonstrated recently that, for non-truncated data, the directional-total-variation (DTV) algorithm can reconstruct images with significantly reduced artifacts from LAR data. In this work, we developed and tailored the DTV algorithm for image reconstruction from truncated LAR data collected with a scanning configuration employing an offset-detector. We carried out a study on image reconstruction for a number of LAR scanning configurations with an offset-detector of practical interest. The study results demonstrate that the DTV algorithm can be tailored to yield, from truncated LAR data, images with significantly reduced artifacts that are observed otherwise in images obtained with existing analytical-based algorithms.