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Title: Hybrid Object Detection System for X-ray Radiographs.


Abstract not provided.

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Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
Report Number(s):
DOE Contract Number:
Resource Type:
Resource Relation:
Conference: Proposed for presentation at the SPIE Optics+Photonics held August 27 - September 2, 2016 in San Diego, CA.
Country of Publication:
United States

Citation Formats

Jimenez, Edward Steven,, Wantuch, Andrew Charles, and Vita, Joshua. Hybrid Object Detection System for X-ray Radiographs.. United States: N. p., 2016. Web.
Jimenez, Edward Steven,, Wantuch, Andrew Charles, & Vita, Joshua. Hybrid Object Detection System for X-ray Radiographs.. United States.
Jimenez, Edward Steven,, Wantuch, Andrew Charles, and Vita, Joshua. Thu . "Hybrid Object Detection System for X-ray Radiographs.". United States. doi:.
title = {Hybrid Object Detection System for X-ray Radiographs.},
author = {Jimenez, Edward Steven, and Wantuch, Andrew Charles and Vita, Joshua},
abstractNote = {Abstract not provided.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Thu Sep 01 00:00:00 EDT 2016},
month = {Thu Sep 01 00:00:00 EDT 2016}

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  • Abstract not provided.
  • Digital x-ray radiography and computed tomography methods are commonly used to characterize mesoscale objects (mm size objects with {micro}m size features). However the ability of these methods to provide high spatial resolution images is dependent, in part, on object recovery algorithms that account for phase effects [1]. The objective of this work is the development and validation of algorithms to model phase-contrast effects observed in x-ray radiographic systems, and to use these algorithms for quantitative object recovery. This work has three distinct tasks. First, we are modifying HADES [2,3] to model x-ray phase contrast and are investigating whether multislice techniquesmore » within the object are needed to fully capture the physics seen in x-ray data. Second, we are developing object recovery approaches. Third, we are validating these simulations against x-ray systems using well-known objects. At the end of this R&D, we will have a set of validated x-ray forward modeling codes including the effects of phase and an understanding of the current object recovery methods limitations.« less
  • Abstract not provided.
  • Abstract not provided.
  • An automated system was built to analyze x-ray radiographs of laser fusion targets which greatly facilitates the detection of coating thickness variations. Many laser fusion targets reqire opaque coatings 1 to 20 thick which have been deposited on small glass balloons 100 to 500 in diameter. These coatings must be uniformly thick to 1% for the targets to perform optimally. Our system is designed to detect variations as small as 100 A in coatings by converting the optical density variations of contact x-ray radiographs into coating thickness variations. Radiographic images are recorded in HRP emulsions and magnifiedmore » by an optical microscope, imaged onto television camera, digitized and processed on a Data General S/230 computer with a code by Whitman. After an initial set-up by the operator, as many as 200 targets will be automatically characterized.« less