Projection extension for region of interest imaging in cone-beam CT

For 3D X-ray imaging during interventions, changes of the imaged object are often restricted to a small part of the field of view, suggesting region of interest (ROI) imaging by irradiating this area only. In this article, we present a novel method for extension of truncated projections in order to avoid truncation artifacts in C-arm based 3D ROI imaging.

The method makes use of prior knowledge by combining forward projections of a previously acquired, nontruncated 3D reference image with the truncated ROI projections. Rigid registration between the two datasets is achieved by using a technique based on local cross-correlation. To account for a gray value mismatch between the two data sets due to, e.g., differing beam quality and different contributions of scattered radiation, a linear gray level transformation is applied to the forward-projected reference data.

The performance of different gray value transformation schemes is systematically assessed by means of numerical simulations. For various simulated scenarios, the best performing transformation has been identified, providing practical guidelines for selecting a scheme depending on the origin of the gray-level mismatch. Experiments prove the high performance of the developed method.

The presented technique enables almost artifact-free 3D ROI imaging during interventions. This actually allows for repeated scans at low dose and enables intraprocedural imaging of large objects even with a small detector. However, applicability of the method is limited to scenarios where direct access to a reference image, e.g., a prior CT scan, is available.