Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation

Search Page

Filters

My Custom Filters

Publication date

Text availability

Article attribute

Article type

Additional filters

Article Language

Species

Sex

Age

Other

Search Results

16 results

Filters applied: . Clear all
Results are displayed in a computed author sort order. The Publication Date timeline is not available.
Page 1
Subclinical cardiac impairment relates to traditional pulmonary function test parameters and lung volume as derived from whole-body MRI in a population-based cohort study.
von Krüchten R, Lorbeer R, Schuppert C, Storz C, Mujaj B, Schulz H, Kauczor HU, Peters A, Bamberg F, Karrasch S, Schlett CL. von Krüchten R, et al. Among authors: schuppert c. Sci Rep. 2021 Aug 9;11(1):16173. doi: 10.1038/s41598-021-95655-7. Sci Rep. 2021. PMID: 34373570 Free PMC article.
Whole-Body Magnetic Resonance Imaging in the Large Population-Based German National Cohort Study: Predictive Capability of Automated Image Quality Assessment for Protocol Repetitions.
Schuppert C, Krüchten RV, Hirsch JG, Rospleszcz S, Hoinkiss DC, Selder S, Köhn A, Stackelberg OV, Peters A, Völzke H, Kröncke T, Niendorf T, Forsting M, Hosten N, Hendel T, Pischon T, Jöckel KH, Kaaks R, Bamberg F, Kauczor HU, Günther M, Schlett CL; German National Cohort MRI Study Investigators. Schuppert C, et al. Invest Radiol. 2022 Jul 1;57(7):478-487. doi: 10.1097/RLI.0000000000000861. Epub 2022 Feb 21. Invest Radiol. 2022. PMID: 35184102
Fully Automated Assessment of Cardiac Chamber Volumes and Myocardial Mass on Non-Contrast Chest CT with a Deep Learning Model: Validation Against Cardiac MR.
Schmitt R, Schlett CL, Sperl JI, Rapaka S, Jacob AJ, Hein M, Hagar MT, Ruile P, Westermann D, Soschynski M, Bamberg F, Schuppert C. Schmitt R, et al. Among authors: schuppert c. Diagnostics (Basel). 2024 Dec 21;14(24):2884. doi: 10.3390/diagnostics14242884. Diagnostics (Basel). 2024. PMID: 39767245 Free article.
Photon-Counting Detector CT: Advances and Clinical Applications in Cardiovascular Imaging.
Hagar MT, Schlett CL, Oechsner T, Varga-Szemes A, Emrich T, Chen XY, Kravchenko D, Tremamunno G, Vecsey-Nagy M, Molina-Fuentes MF, Krauss T, Taron J, Schuppert C, Bamberg F, Soschynski M. Hagar MT, et al. Among authors: schuppert c. Rofo. 2024 Nov 20. doi: 10.1055/a-2452-0288. Online ahead of print. Rofo. 2024. PMID: 39566513 English, German.
Evaluating small coronary stents with dual-source photon-counting computed tomography: effect of different scan modes on image quality and performance in a phantom.
Stein T, von Zur Muhlen C, Verloh N, Schürmann T, Krauss T, Soschynski M, Westermann D, Taron J, Can E, Schlett CL, Bamberg F, Schuppert C, Hagar MT. Stein T, et al. Among authors: schuppert c. Diagn Interv Radiol. 2025 Jan 1;31(1):29-38. doi: 10.4274/dir.2024.242893. Epub 2024 Oct 21. Diagn Interv Radiol. 2025. PMID: 39463047 Free PMC article.
Accuracy of a deep learning-based algorithm for the detection of thoracic aortic calcifications in chest computed tomography and cardiovascular surgery planning.
Saffar R, Sperl JI, Berger T, Vojtekova J, Kreibich M, Hagar MT, Weiss JB, Soschynski M, Bamberg F, Czerny M, Schuppert C, Schlett CL. Saffar R, et al. Among authors: schuppert c. Eur J Cardiothorac Surg. 2024 Jun 3;65(6):ezae219. doi: 10.1093/ejcts/ezae219. Eur J Cardiothorac Surg. 2024. PMID: 38837348
16 results