Materials analysis using x-ray linear attenuation coefficient measurements at four photon energies.
The analytical properties of an accurate parameterization scheme for the x-ray linear attenuation coefficient are examined. The parameterization utilizes an additive combination of N compositional- and energy-dependent coefficients. The former were derived from a parameterization of elemental cross-sections using a polynomial in atomic number. The compositional-dependent coefficients are referred to as the mixture parameters, representing the electron density and higher order statistical moments describing elemental distribution. Additivity is an important property of the parameterization, allowing measured x-ray linear attenuation coefficients to be written as linear simultaneous equations, and then solved for the unknown coefficients. The energy-dependent coefficients can be determined by calibration from measurements with materials of known composition. The inverse problem may be utilized for materials analysis, whereby the simultaneous equations represent multi-energy linear attenuation coefficient measurements, and are solved for the mixture parameters. For in vivo studies, the choice of measurement energies is restricted to the diagnostic region (approximately 20 keV to 150 keV), where the parameterization requires N >or= 4 energies. We identify a mathematical pathology that must be overcome in order to solve the inverse problem in this energy regime. An iterative inversion strategy is presented for materials analysis using four or more measurements, and then tested against real data obtained at energies 32 keV to 66 keV. The results demonstrate that it is possible to recover the electron density to within +/-4% and fourth mixture parameter. It is also a key finding that the second and third mixture parameters cannot be recovered, as they are of minor importance in the parameterization at diagnostic x-ray energies.
Midgley
S M
SM
School of Physics, Monash University, Clayton, VIC 3800, Australia. stewart.midgley@spme.monash.edu.au
D015502:Absorptiometry, Photon / Q000379:methods*; D000465:Algorithms; D001672:Biocompatible Materials / Q000032:analysis* / Q000737:chemistry*; D003198:Computer Simulation; D018499:Linear Energy Transfer; D008422:Materials Testing / Q000379:methods*; D008956:Models, Chemical; D017785:Photons; D012542:Scattering, Radiation
D001672:Biocompatible Materials