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X-Ray Tomography

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA8571-19-P-A016
Agency Tracking Number: F183-021-0424
Amount: $149,951.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: AF183-021
Solicitation Number: 2018.3
Timeline
Solicitation Year: 2018
Award Year: 2019
Award Start Date (Proposal Award Date): 2019-04-08
Award End Date (Contract End Date): 2020-04-08
Small Business Information
6154 McLendon Court, Alexandria, VA, 22310
DUNS: 044123414
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: Y
Principal Investigator
 Dr. John Tan
 (703) 982-7777
 jtan@scix3.com
Business Contact
 Dr. John Tan
Phone: (703) 982-7777
Email: jtan@scix3.com
Research Institution
N/A
Abstract
CSLabs develops XDLayer (X-ray DeLayer) as an automated software framework to non-destructively analyze Printed Circuit Boards (PCB's) using lab x-ray microscope systems. XDLayer performs automated sample scanning with optimized 2D and 3D image analysis algorithms to maximize overall system throughput by minimizing the number of viewing angles and exposure times needed to analyze a given PCB, while scanning feedback and image analysis of the PCB during acquisition ensures high quality reconstruction. XDLayer forms the basis of a scalable, extensible platform for reverse engineering, failure analysis, and change detection (Trust) of PCBs. Trade space parameter optimization based on rigorous physics-based simulation enables comprehensive XDLayer algorithm development, including image-stitching, limited-view computed tomography, and 3D segmentation and classification for PCB structures. Key innovations in XDLayer technologies allow optimization across the processing chain, combining iterative computed tomography methods with machine learning driven classification and segmentation methods, using as priors, the expected structures of PCBs such as planar wiring, and multi-class density classifications. These optimizations enable high quality PCB reconstruction while reducing analysis times compared with conventional computed tomography algorithms, managing high density materials on flux-limited microscope systems.

* Information listed above is at the time of submission. *

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