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Proceedings Paper

Focal spot deconvolution using convolutional neural networks
Author(s): Jan Kuntz; Joscha Maier; Marc Kachelrieß; Stefan Sawall
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Paper Abstract

The focal spot size of x-ray tubes as well as the pixel size and scintillator thickness limit the spatial resolution of projection images as they result in blurring and degradation of the system’s point spread function. Deblurring of those images has been a topic of research for several decades. However, it is not solved in general. In this manuscript the application of a convolutional neural network for the deblurring of x-ray projection images is presented and compared to a standard deblurrig technique. The advantages of the neural network in terms of image quality and applicability are demonstrated with simulations and measurements originating from table top and gantry based micro-CT systems.

Paper Details

Date Published: 1 March 2019
PDF: 6 pages
Proc. SPIE 10948, Medical Imaging 2019: Physics of Medical Imaging, 109480Q (1 March 2019); doi: 10.1117/12.2513400
Show Author Affiliations
Jan Kuntz, Deutsches Krebsforschungszentrum (Germany)
Joscha Maier, Ruprecht-Karls Univ. (Germany)
Marc Kachelrieß, Deutsches Krebsforschungszentrum (Germany)
Stefan Sawall, Deutsches Krebsforschungszentrum (Germany)


Published in SPIE Proceedings Vol. 10948:
Medical Imaging 2019: Physics of Medical Imaging
Taly Gilat Schmidt; Guang-Hong Chen; Hilde Bosmans, Editor(s)

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