Image reconstruction from partially truncated data over limited-angular-ranges

In cone-beam computed tomography (CBCT) imaging, a scanning configuration with an offset-detector is often used for extending the field of view (FOV) of the system. Due to the truncation of data at certain views, data are required to be collected over a full angular range (FAR) of 360 for accurate reconstruction by use of existing analytical-based algorithms. However, there exist interests in practical applications for limited-angular-range (LAR) imaging because it may allow for the reduction of radiation dose and scanning time and for the avoidance of the collisions between the moving gantry and scanned objects. Under such imaging conditions, existing algorithms generally yield reconstructions with significant artifacts. In this work, we develop and investigate a directional-total-variation (DTV) algorithm for image reconstruction from partially truncated data collected over LARs. By using the DTV algorithm, we have performed numerical simulation studies with partially truncated data collected from a pelvic phantom over different LARs with an offset-detector CBCT system. The results of the numerical studies demonstrate that the proposed algorithm can yield, from partially truncated LAR data, images with significantly reduced artifacts that are observed otherwise in images obtained with existing analytical-based algorithms.