Incidental vertebral fracture prediction using neuronal network-based automatic spine segmentation and volumetric bone mineral density extraction from routine clinical CT scans.

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Title:	Incidental vertebral fracture prediction using neuronal network-based automatic spine segmentation and volumetric bone mineral density extraction from routine clinical CT scans.
Authors:	Bodden J; Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany., Dieckmeyer M; Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.; Department of Diagnostic and Interventional Neuroradiology, University of Bern, Bern, Switzerland., Sollmann N; Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.; TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.; Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany., Burian E; Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany., Rühling S; Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany., Löffler MT; Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.; Department of Diagnostic and Interventional Radiology, University Medical Center Freiburg, Freiburg im Breisgau, Germany., Sekuboyina A; Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.; Department of Informatics, Technical University of Munich, Munich, Germany.; Munich School of BioEngineering, Technical University of Munich, Munich, Germany., El Husseini M; Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.; Department of Informatics, Technical University of Munich, Munich, Germany., Zimmer C; Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.; TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany., Kirschke JS; Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.; TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany., Baum T; Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
Source:	Frontiers in endocrinology [Front Endocrinol (Lausanne)] 2023 Jul 17; Vol. 14, pp. 1207949. Date of Electronic Publication: 2023 Jul 17 (Print Publication: 2023).
Publication Type:	Journal Article; Research Support, Non-U.S. Gov't
Journal Info:	Publisher: Frontiers Research Foundation] Country of Publication: Switzerland NLM ID: 101555782 Publication Model: eCollection Cited Medium: Print ISSN: 1664-2392 (Print) Linking ISSN: 16642392 NLM ISO Abbreviation: Front Endocrinol (Lausanne) Subsets: MEDLINE
Database:	MEDLINE Ultimate

Description
ISSN:	1664-2392
DOI:	10.3389/fendo.2023.1207949