Multi energy computed tomography imaging optimization

Raziye Kubra Kumrular; Thomas Blumensath

doi:10.1117/12.2611731

4 April 2022 Multi energy computed tomography imaging optimization

Raziye Kubra Kumrular, Thomas Blumensath

Proceedings Volume 12031, Medical Imaging 2022: Physics of Medical Imaging; 120312R (2022) https://doi.org/10.1117/12.2611731
Event: SPIE Medical Imaging, 2022, San Diego, California, United States

Conference Poster

Abstract

We proposed the optimization of a more generic X-ray tomography model. By imaging an object with a range of source spectra, we showed that spectral images could nevertheless be obtained, even if we have energy blind detectors. For observations to be integrated over energy levels, we tried to solve the problem by jointly estimating the X-ray measurement and X-ray absorption spectrum under the constraint. The research includes using DL (deep-learning) to learn a low-dimensional model of absorption spectra, using DL constraint to recover absorption spectra from X-ray measurements, and using DL to decompose absorption spectra estimates into material density estimates.

Conference Presentation

Citation Download Citation

Raziye Kubra Kumrular and Thomas Blumensath "Multi energy computed tomography imaging optimization", Proc. SPIE 12031, Medical Imaging 2022: Physics of Medical Imaging, 120312R (4 April 2022); https://doi.org/10.1117/12.2611731

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