View in EDS HTML Full Text PDF Full Text

Validation of an automated AI-based micro-CT organ segmentation workflow against expert annotations and its impact on fluorescence quantification.

Saved in:
Bibliographic Details
Title: Validation of an automated AI-based micro-CT organ segmentation workflow against expert annotations and its impact on fluorescence quantification.
Authors: Rama E; Institute for Experimental Molecular Imaging, Faculty of Medicine, RWTH Aachen University, Aachen, Germany., Yu S; Institute for Experimental Molecular Imaging, Faculty of Medicine, RWTH Aachen University, Aachen, Germany., Schraven S; Institute for Experimental Molecular Imaging, Faculty of Medicine, RWTH Aachen University, Aachen, Germany.; Gremse-IT GmbH, Aachen, Germany., Gurberg Z; Gremse-IT GmbH, Aachen, Germany., Savina E; Institute for Experimental Molecular Imaging, Faculty of Medicine, RWTH Aachen University, Aachen, Germany., Liu J; Institute for Experimental Molecular Imaging, Faculty of Medicine, RWTH Aachen University, Aachen, Germany., Magnuska ZA; Institute for Experimental Molecular Imaging, Faculty of Medicine, RWTH Aachen University, Aachen, Germany.; Department of Anaesthesia, Intensive Care Medicine and Pain Medicine, Medical University of Vienna, Vienna, Austria., Gremse F; Gremse-IT GmbH, Aachen, Germany., Kiessling F; Institute for Experimental Molecular Imaging, Faculty of Medicine, RWTH Aachen University, Aachen, Germany. fkiessling@ukaachen.de.
Source: European radiology experimental [Eur Radiol Exp] 2026 May 29; Vol. 10 (1). Date of Electronic Publication: 2026 May 29.
Publication Type: Journal Article; Validation Study
Journal Info: Publisher: SpringerOpen Country of Publication: England NLM ID: 101721752 Publication Model: Electronic Cited Medium: Internet ISSN: 2509-9280 (Electronic) Linking ISSN: 25099280 NLM ISO Abbreviation: Eur Radiol Exp Subsets: MEDLINE
Database: MEDLINE Ultimate
Full text is not displayed to guests.
Description
ISSN:2509-9280
DOI:10.1186/s41747-026-00742-x