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SAMDAILY.US - ISSUE OF MARCH 14, 2024 SAM #8143
SPECIAL NOTICE

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

Notice Date
3/12/2024 8:48:10 AM
 
Notice Type
Special Notice
 
NAICS
334517 — Irradiation Apparatus Manufacturing
 
Contracting Office
LLNS � DOE CONTRACTOR Livermore CA 94551 USA
 
ZIP Code
94551
 
Solicitation Number
IL-13625
 
Response Due
4/12/2024 9:00:00 AM
 
Archive Date
04/27/2024
 
Point of Contact
Mary Holden-Sanchez, Phone: 9254224614, Charlotte Eng, Phone: 9254221905
 
E-Mail Address
holdensanchez2@llnl.gov, eng23@llnl.gov
(holdensanchez2@llnl.gov, eng23@llnl.gov)
 
Description
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: Company Name and address. The name, address, and telephone number of a point of contact. 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
 
Web Link
SAM.gov Permalink
(https://sam.gov/opp/dc10559641fd44e991974487ee5a0b04/view)
 
Place of Performance
Address: Livermore, CA, USA
Country: USA
 
Record
SN06993527-F 20240314/240312230047 (samdaily.us)
 
Source
SAM.gov Link to This Notice
(may not be valid after Archive Date)

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