3D Image Reconstruction from X-Ray Measurements with Overlap
This addresses a bottleneck in scanner design for medical imaging and security, enabling more flexible geometries without overlap restrictions, though it is incremental as it builds on existing reconstruction methods.
The paper tackles 3D image reconstruction from X-ray projections with overlapping rays, a problem arising from multi-source scanners, by deriving a nonlinear constraint model and solving it with an algorithm, showing highly improved results in experiments.
3D image reconstruction from a set of X-ray projections is an important image reconstruction problem, with applications in medical imaging, industrial inspection and airport security. The innovation of X-ray emitter arrays allows for a novel type of X-ray scanners with multiple simultaneously emitting sources. However, two or more sources emitting at the same time can yield measurements from overlapping rays, imposing a new type of image reconstruction problem based on nonlinear constraints. Using traditional linear reconstruction methods, respective scanner geometries have to be implemented such that no rays overlap, which severely restricts the scanner design. We derive a new type of 3D image reconstruction model with nonlinear constraints, based on measurements with overlapping X-rays. Further, we show that the arising optimization problem is partially convex, and present an algorithm to solve it. Experiments show highly improved image reconstruction results from both simulated and real-world measurements.