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.
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LLNL’s novel approach utilizes a number of techniques to improve reconstruction accuracy:
For this method, a Silicon on Insulator (SOI) wafer is used to tailor etch rates and thickness in initial steps of the process. The simple three step process approach is comprised of grayscale lithography, deep reactive-ion etch (DRIE) and liftoff of the SOI wafer. The liftoff process is used to dissolve the insulating layer, thus separating sections of the wafer as individual silicon…
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 pioneered the use of tomographic reconstruction to determine the power density of electron beams using profiles of the beam taken at a number of angles. LLNL’s earlier diagnostic consisted of a fixed number of radially oriented sensor slits and required the beam to be circled over them at a fixed known diameter to collect data. The new sensor design incorporates annular slits instead,…
LLNL has developed a compact and low-power cantilever-based sensor array, which has been used to detect various vapor-phase analytes. For further information on the latest developments, see the article "Sniffing the Air with an Electronic Nose."