Stereo X-Ray Tomography

X-ray tomography is a powerful volumetric imaging technique, but detailed 3-D imaging requires the acquisition of a large number of individual X-ray images, which is time consuming. For applications where spatial information needs to be collected quickly, for example, when studying dynamic processes, standard X-ray tomography is therefore not applicable. Inspired by stereo vision, in this article, we develop X-ray imaging methods that work with two X-ray projection images. In this setting, without the use of additional strong prior information, we no longer have enough information to fully recover the 3-D tomographic images. However, up to a point, we are nevertheless able to extract spatial locations of point and line features. From stereo vision, it is well known that, for a known imaging geometry, once the same point is identified in two images taken from different directions, then the point’s location in 3-D space is exactly specified. The challenge is the matching of points between images. As X-ray transmission images are fundamentally different from the surface reflection images used in standard computer vision, we here develop a different feature identification and matching approach. In fact, once point-like features are identified, if there are limited points in the image, then they can often be matched exactly. In fact, by utilizing a third observation from an appropriate direction, matching becomes unique. Once matched, point locations in 3-D space are easily computed using geometric considerations. Linear features, with clear end points, can be located using a similar approach.