New deep learning paper on Clinical CT from our group: Evaluating renal lesions using deep-learning based extension of dual-energy FoV in dual-source CT—A retrospective pilot study.
Eur J Radiol. 2021 Jun;139:109734. doi: 10.1016/j.ejrad.2021.109734. Epub 2021
The code is available at: https://gitlab.oit.duke.edu/dpc18/duke-ct-spectral-extrapolation. It includes code for both of our DE extrapolation papers:
(1) Clark, D. P., Schwartz, F. R., Marin, D., Ramirez‐Giraldo, J. C., & Badea, C. T. (2020). Deep learning based spectral extrapolation for dual‐source, dual‐energy x‐ray computed tomography. Medical Physics, 47(9), 4150-4163.
(2) Schwartz, F. R., Clark, D. P., Ding, Y., Ramirez-Giraldo, J. C., Badea, C. T., & Marin, (2021). Evaluating renal lesions using deep-learning based extension of dual-energy FoV in dual-source CT – a retrospective pilot study. European Journal of Radiology, 109734.
