This invention proposes achieving the same effect of a single, high intensity pulse through the use of a closely spaced burst of short duration pulses. By keeping the intensity of the individual pulses below the damage threshold the risk of catastrophic damage is greatly mitigated. Additionally, the pulses are directed to strike the target at locations temporally and spatially sufficiently…

This invention proposes the use of a nonlinear spectral broadening subsystem as a post-CPA pulse compression add-on for high energy laser systems. The proposed solution utilizes the beam profile of a high peak power laser as a reference to shape a highly transmissive nonlinear plastic (e.g., CR39) itself to ensure a spatially homogeneous nonlinear spectral broadening.

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.

Lawrence Livermore National Laboratory (LLNL) is offering the opportunity to collaborate in accelerating artificial intelligence (AI) for applied science, including research in key areas such as advanced material design, 3D printing, predictive biology, energy systems, “self-driving” lasers and fusion energy research.

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…

Clinical images have a wealth of data that are currently untapped by physicians and machine learning (ML) methods alike. Most ML methods require more data than is available to sufficiently train them. In order to obtain all data contained in a clinical image, it is imperative to be able to utilize multimodal, or various types of, data such as tags or identifications, especially where spatial…

Some COVID-19 diagnoses are utilizing computed tomography (CT)-scans for triage. CT-scans produce immediate results with high sensitivity. The digital images produced by a CT-scan require physicians to identify objects within the image to determine the presence of disease. Object identification can be done using machine learning (ML) techniques such as deep learning (DL) to improve speed and…

MimicGAN represents a new generation of methods that can “self-correct” for unseen corruptions in the data out in the field. This is particularly useful for systems that need to be deployed autonomously without needing constant intervention such as Automated Driver Assistance Systems. MimicGAN achieves this by treating every test sample as “corrupt” by default. The goal is to determine (a) the…

LLNL has developed a new system, called the Segmentation Ensembles System, that provides a simple and general way to fuse high-level and low-level information and leads to a substantial increase in overall performance of digital image analysis. LLNL researchers have demonstrated the effectiveness of the approach on applications ranging from automatic threat detection for airport security, to…

The SLIDER deflector includes a waveguide, a serrated mask positioned above the waveguide cladding, and a synchronized pump beam. The pump beam illuminates the serrated mask with a short pulse and transfers its pattern to the guiding layer where it imprints a sequence of prisms. The prisms are activated via nonlinear optical effects in the semiconductor and persist for the duration of the…