Comparison of three reconstruction methods based on deconvolution, iterative algorithm and neural network for X-ray fluorescence imaging with coded aperture optics
Anicó Kulow, Ana Guilherme Buzanich, Uwe Reinholz, Franziska Emmerling, Sven Hampel, Ursula E. A. Fittschen, Christina Streli, Martin Radtke
Abstract
Superimposed images acquired by XRF with coded aperture optics can be recovered successfully iteratively.
Topics & Concepts
DeconvolutionCoded apertureAperture (computer memory)OpticsArtificial neural networkFluorescenceIterative reconstructionAlgorithmComputer sciencePhysicsArtificial intelligenceDetectorAcousticsMedical Imaging Techniques and ApplicationsAdvanced X-ray Imaging TechniquesAdvanced X-ray and CT Imaging