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.
Keywords
- Show all (101)
- Additive Manufacturing (37)
- Photoconductive Semiconductor Switches (PCSS) (9)
- Imaging Systems (8)
- 3D Printing (7)
- Semiconductors (6)
- Optical Switches (4)
- Electric Grid (3)
- Power Electronics (3)
- Sensors (3)
- Manufacturing Automation (2)
- MEMS Sensors (2)
- Optical Sensors (2)
- Particle Accelerators (2)
- Spectrometers (2)
- Synthesis and Processing (2)
- Manufacturing Simulation (1)
- Volumetric Additive Manufacturing (1)
- (-) Manufacturing Improvements (3)
- (-) Computing (2)
- (-) Precision Engineering (2)
LLNL’s novel approach utilizes a number of techniques to improve reconstruction accuracy:
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…
Recent advancements in additive manufacturing, also called 3D printing, allow precise placement of materials in three dimensions. LLNL researchers have invented mechanical logic gates based on flexures that can be integrated into the microstructure of a micro-architected material through 3D printing. The logic gates can be combined into circuits allowing complex logic operations to be…
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,…
The LLNL method for optimizing as built optical designs uses insights from perturbed optical system theory and reformulates perturbation of optical performance in terms of double Zernikes, which can be calculated analytically rather than by tracing thousands of rays. A new theory of compensation is enabled by the use of double Zernikes which allows the performance degradation of a perturbed…