3D tomography reconstruction improved by integrating view registration.

ABSTRACT

Tomographic measurements involve two steps: view registration (VR) to determine the orientation of the projections and the subsequent tomography reconstruction. Therefore, the practical error in both steps impacts the overall accuracy of the final tomographic measurements. Past work treated these two steps separately. This work shows that the overall tomography accuracy can be enhanced substantially if these two steps are considered holistically because there is an opportunity for each step to leverage the information in the other step to improve the overall accuracy if they are considered holistically. Based on this recognition, this work has developed a new method called the reconstruction integration view registration (RIVR) method to implement such a holistic scheme. The key of this implementation involved the use of the Metropolis criterion to adjust the initial orientation provided by the traditional VR process dynamically. Both controlled experiments and accompanying numerical analyses were conducted to validate the RIVR method. Two sets of controlled experiments were conducted and analyzed, including a static uniform dye solution and turbulent flows, where the RIVR technique was demonstrated to significantly reduce the overall reconstruction error (by ∼37% and ∼35%, respectively) compared to past methods that treated VR and tomography separately.