California Bids > Bid Detail

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

Agency:
Level of Government: Federal
Category:
  • 99 - Miscellaneous
  • A - Research and development
  • R - Professional, Administrative and Management Support Services
Opps ID: NBD00159375113299310
Posted Date: Mar 12, 2024
Due Date: Apr 12, 2024
Source: https://sam.gov/opp/dc10559641...
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TECHNOLOGY/BUSINESS OPPORTUNITY Dynamic 4DCT Reconstruction using Neural Representation-based Optimization
Active
Contract Opportunity
Notice ID
IL-13625
Related Notice
Department/Ind. Agency
ENERGY, DEPARTMENT OF
Sub-tier
ENERGY, DEPARTMENT OF
Office
LLNS – DOE CONTRACTOR
General Information View Changes
  • Contract Opportunity Type: Special Notice (Updated)
  • All Dates/Times are: (UTC-07:00) PACIFIC STANDARD TIME, LOS ANGELES, USA
  • Updated Published Date: Mar 12, 2024 08:48 am PDT
  • Original Published Date: Mar 12, 2024 08:29 am PDT
  • Updated Response Date: Apr 12, 2024 09:00 am PDT
  • Original Response Date: Apr 12, 2024 09:00 am PDT
  • Inactive Policy: 15 days after response date
  • Updated Inactive Date: Apr 27, 2024
  • Original Inactive Date: Apr 27, 2024
  • Initiative:
Classification
  • Original Set Aside:
  • Product Service Code:
  • NAICS Code:
    • 334517 - Irradiation Apparatus Manufacturing
  • Place of Performance:
    Livermore , CA
    USA
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:






  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


Attachments/Links
Contact Information View Changes
Contracting Office Address
  • 7000 East Avenue
  • Livermore , CA 94551
  • USA
Primary Point of Contact
Secondary Point of Contact
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