The characterization of in vivo urinary phospate stones by spectral CT
Author:
Publisher
Springer Science and Business Media LLC
Subject
Urology
Link
https://link.springer.com/content/pdf/10.1007/s00240-022-01388-1.pdf
Reference29 articles.
1. Zheng J, Yu H, Batur J et al (2021) A multicenter study to develop a non-invasive radiomic model to identify urinary infection stone in vivo using machine-learning. Kidney Int 100:870–880. https://doi.org/10.1016/j.kint.2021.05.031
2. Khan SR, Pearle MS, Robertson WG et al (2016) Kidney stones. Nat Rev Dis Primers 2:16008. https://doi.org/10.1038/nrdp.2016.8
3. Knoll T, Schubert AB, Fahlenkamp D, Leusmann DB, Wendt-Nordahl G, Schubert G (2011) Urolithiasis through the ages: data on more than 200,000 urinary stone analyses. J Urol 185:1304–1311. https://doi.org/10.1016/j.juro.2010.11.073
4. Daudon M, Bouzidi H, Bazin D (2010) Composition and morphology of phosphate stones and their relation with etiology. Urol Res 38:459–467. https://doi.org/10.1007/s00240-010-0320-3
5. Türk C, Petřík A, Sarica K et al (2016) EAU guidelines on diagnosis and conservative management of urolithiasis. Eur Urol 69:468–474. https://doi.org/10.1016/j.eururo.2015.07.040
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