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Found 5 papers, 0 papers with code
Deep learning based workflow for accelerated industrial X-ray Computed Tomography
Furthermore, traditional workflows based on using analytic reconstruction algorithms require a large number of projections for accurate characterization - leading to longer measurement times and hindering the adoption of XCT for in-line inspections.
Design of Novel Loss Functions for Deep Learning in X-ray CT
Particularly in a field such as X-ray CT, where radiologists' subjective preferences in image characteristics are key to acceptance, it may be desirable to penalize differences in DL more creatively.
Statistically Adaptive Filtering for Low Signal Correction in X-ray Computed Tomography
But low dose comes with a cost of low signal artifacts such as streaks and low frequency bias in the reconstruction.
MBIR Training for a 2.5D DL network in X-ray CT
The cost we have to pay is that MBIR is computationally expensive.
Direct Iterative Reconstruction of Multiple Basis Material Images in Photon-counting Spectral CT
This work is meant to lay the foundation for further work with phantoms including spatially coincident mixtures of contrast materials and/or contrast agents in widely varying concentrations, molecular imaging from animal scans, and eventually clinical applications.
