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- W3131502735 abstract "The feasibility of acquiring multi-energy CT data through slow modulation of the kVp as an alternative to photon-counting detectors (PCDs) is currently under exploration. A low kVp-switching rate can be enabled with a conventional CT system but raises challenges due to missing sinogram views. Our previous work used a CNN-based method for sinogram completion by generating full-sampled images from undersampled sinograms, providing an acceptable image quality at a 22°/kVp switching rate. The purpose of this study was to investigate a GAN-based spectral sinogram completion method for enabling a lower kVp switching rate. A Pix2Pix GAN model with paired undersampled sinogram of 45° or 120° projections/kVp and its corresponding full-sampled sinogram was implemented and trained. The completed data was subsequently used to perform sinogram domain material decomposition. Our results on a simulated FORBILD abdomen phantom dataset showed that the GAN-based method can further lower the kVp switching rate to 45° projections/kVp. The proposed GAN-based sinogram completion method facilitates slow-kVp switching acquisitions and thus further relaxes hardware requirements." @default.
- W3131502735 created "2021-03-01" @default.
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- W3131502735 date "2021-02-15" @default.
- W3131502735 modified "2023-09-23" @default.
- W3131502735 title "GAN-based sinogram completion for slow triple kVp switching CT" @default.
- W3131502735 doi "https://doi.org/10.1117/12.2580735" @default.
- W3131502735 hasPublicationYear "2021" @default.
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