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Evaluation of magnetic resonance imaging and deep learning-based synthetic computed tomography for calcified intradural tumors – importance of domain-specific training and validation of synthetic imaging methods for clinical application

Crossref DOI link: https://doi.org/10.1007/s00701-025-06731-0

Published Online: 2025-12-11

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Fischer, Gregor

Stengel, Felix C.

Bertulli, Lorenzo

Bättig, Linda

Staartjes, Victor E.

Dietrich, Tobias

Kim, Olaf Chan-Hi

Stienen, Martin N.
Funding

Funding for this research was provided by:

MRIguidance (no ID)

University of Zurich
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Text and Data Mining valid from 2025-12-11

Version of Record valid from 2026-01-05
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Article History

Received: 21 May 2025

Accepted: 18 November 2025

First Online: 11 December 2025

Declarations

:

: The study was approved by the institutional review board of St.Gallen (BASEC 2022-D0025). All patients provided written informed consent. All procedures performed were in accordance with the ethical standards of St.Gallen and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

: The authors declare no competing interests.

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