Leveraging multi-channel x-ray detector technology to improve quality metrics for industrial and security applications

Sandia National Laboratories has recently developed the capability to acquire multi-channel radio- graphs for multiple research and development applications in industry and security. This capability allows for the acquisition of x-ray radiographs or sinogram data to be acquired at up to 300 keV with up to 128 channels per pixel. This work will investigate whether multiple quality metrics for computed tomography can actually benefit from binned projection data compared to traditionally acquired grayscale sinogram data. Features and metrics to be evaluated include the ability to dis- tinguish between two different materials with similar absorption properties, artifact reduction, and signal-to-noise for both raw data and reconstructed volumetric data. The impact of this technology to non-destructive evaluation, national security, and industry is wide-ranging and has to potential to improve upon many inspection methods such as dual-energy methods, material identification, object segmentation, and computer vision on radiographs.

[1]  Edward Steven Jimenez,et al.  Exploring mediated reality to approximate x-ray attenuation coefficients from radiographs , 2014, Optics & Photonics - Optical Engineering + Applications.

[2]  Edward Steven Jimenez,et al.  Utilization of Virtualized Environments for Efficient X-ray Attenuation Approximation , 2014 .

[3]  Edward Steven Jimenez,et al.  Developing imaging capabilities of multi-channel detectors comparable to traditional x-ray detector technology for industrial and security applications , 2016, Optical Engineering + Applications.

[4]  Sabee Molloi,et al.  Image-based spectral distortion correction for photon-counting x-ray detectors. , 2012, Medical physics.

[5]  Kyle R. Thompson,et al.  Object composition identification via mediated-reality supplemented radiographs , 2014, 2014 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC).

[6]  G. Blake,et al.  Technical principles of dual energy x-ray absorptiometry. , 1997, Seminars in nuclear medicine.

[7]  Edward Steven Jimenez,et al.  An Experiment for Material Classification using Multichannel Radiographs. , 2015 .

[8]  Katsuyuki Taguchi,et al.  Uniformity correction in photon-counting X-ray detector based on basis material decomposition , 2008, 2008 IEEE Nuclear Science Symposium Conference Record.

[9]  E. Roessl,et al.  K-edge imaging in x-ray computed tomography using multi-bin photon counting detectors , 2007, Physics in medicine and biology.

[10]  Kyle R. Thompson,et al.  Cluster-based approach to a multi-GPU CT reconstruction algorithm , 2014, 2014 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC).

[11]  Kyle R. Thompson,et al.  An Irregular Approach to Large-Scale Computed Tomography on Multiple Graphics Processors Improves Voxel Processing Throughput , 2012, 2012 SC Companion: High Performance Computing, Networking Storage and Analysis.

[12]  R Wurtz,et al.  Metrics for Developing an Endorsed Set of Radiographic Threat Surrogates for JINII/CAARS , 2009 .

[13]  L. Feldkamp,et al.  Practical cone-beam algorithm , 1984 .