TECHNOLOGY/BUSINESS OPPORTUNITY Dynamic 4DCT Reconstruction using Neural Representation-based Optimization

Opportunity:

Lawrence Livermore National Laboratory (LLNL), operated by the Lawrence Livermore National Security (LLNS), LLC under contract no. DE-AC52-07NA27344 (Contract 44) with the U.S. Department of Energy (DOE), is offering the opportunity to enter into a collaboration to further develop and commercialize its Dynamic 4DCT Reconstruction using Neural Representation-based Optimization.

Background:

Reconstructing moving scenes with computed tomography (4DCT) is a challenging and ill-posed problem with important applications in industrial and medical settings.  Dynamic computed tomography (DCT) refers to image reconstruction of moving or non-rigid objects over time while x-ray projections are acquired over a range of angles. Although 4DCT reconstruction is widely applicable to the study of object deformation and dynamics in a number of industrial and clinical applications, it has been a long-standing challenge due to the complexity of the x-ray measurement capturing both spatial and temporal features with the limited data sampling.

Description:

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 enable the reconstruction of the scene with high dynamics, the inventors developed a novel method for dynamic 4DCT reconstruction that leverages implicit neural representations with a parametric motion field to reconstruct dynamic scenes as time-varying sequence of 3D volumes.  The methods have been demonstrated in experiments that reconstruct dynamic scenes with deformable and periodic motion on physically simulated synthetic data and real data.

Advantages/Benefits: 

The principal advantages of this invention are:

• This method is an end-to-end optimization approach without the need for any training data;
• This method eliminates the need for fast CT scanners in use cases where the object or scene being scanned is fast moving;
• The hierarchical coarse-to-fine procedure to estimate the motion field enables recovering fine details of the motion scene without suffering from severe artifacts due to poor convergence of the optimization.

Potential Applications: 

CT/CAT (computerized axial tomography) scanner systems

Development Status: 

Current stage of technology development:  TR-2

LLNL has patent(s) on this invention.

U.S. Patent No. 11,741,643 Reconstruction of dynamic scenes based on differences between collected view and synthesized view published 8/29/2023

LLNL is seeking industry partners with a demonstrated ability to bring such inventions to the market. Moving critical technology beyond the Laboratory to the commercial world helps our licensees gain a competitive edge in the marketplace. All licensing activities are conducted under policies relating to the strict nondisclosure of company proprietary information. 

Please visit the IPO website at https://ipo.llnl.gov/resources for more information on working with LLNL and the industrial partnering and technology transfer process.

Note:  THIS IS NOT A PROCUREMENT.  Companies interested in commercializing LLNL's Dynamic 4DCT Reconstruction using Neural Representation-based Optimization should provide an electronic OR written statement of interest, which includes the following:

1. Company Name and address.
2. The name, address, and telephone number of a point of contact.
3. A description of corporate expertise and/or facilities relevant to commercializing this technology.

Please provide a complete electronic OR written statement to ensure consideration of your interest in LLNL's Dynamic 4DCT Reconstruction using Neural Representation-based Optimization.

The subject heading in an email response should include the Notice ID and/or the title of LLNL’s Technology/Business Opportunity and directed to the Primary and Secondary Point of Contacts listed below.

Written responses should be directed to:

Lawrence Livermore National Laboratory

Innovation and Partnerships Office

P.O. Box 808, L-779

Livermore, CA  94551-0808

Attention:   IL-13625