The essence of this invention is a method that couples network architecture using neural implicit representations coupled with a novel parametric motion field to perform limited angle 4D-CT reconstruction of deforming scenes.

To solve these challenges using new and existing CT system designs, LLNL has developed an innovative software package for CT data processing and reconstruction. Livermore Tomography Tools (LTT) is a modern integrated software package that includes all aspects of CT modeling, simulation, reconstruction, and analysis algorithms based on the latest research in the field. LTT contains the most…

LLNL uses the additive manufacturing technique known as Electrophoretic Deposition to shape the source particle material into a finished magnet geometry. The source particle material is dispersed in a liquid so that the particles can move freely. Electric fields in the shape of the finished product then draw the particles to the desired location to form a “green body”, much like an unfired…

LLNL has developed a new active memory data reorganization engine. In the simplest case, data can be reorganized within the memory system to present a new view of the data. The new view may be a subset or a rearrangement of the original data. As an example, an array of structures might be more efficiently accessed by a CPU as a structure of arrays. Active memory can assemble an alternative…