Reducing manual workload in CT and MRI annotation with the Segment Anything Model 2.

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Title: Reducing manual workload in CT and MRI annotation with the Segment Anything Model 2.
Authors: Misera L; Institute and Polyclinic for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Carl Gustav Carus Dresden, Technical University Dresden, Dresden, Germany.; Else Kroener Fresenius Center for Digital Health, Technical University Dresden, Dresden, Germany., Nebelung S; Department of Diagnostic and Interventional Radiology, University Hospital Aachen, Aachen, Germany., Carrero ZI; Else Kroener Fresenius Center for Digital Health, Technical University Dresden, Dresden, Germany., Bressem K; Department of Diagnostic and Interventional Radiology, Klinikum Rechts der Isar, Technical University of Munich, School of Medicine and Health, TUM University Hospital, Munich, Germany.; Department of Cardiovascular Radiology and Nuclear Medicine, Technical University of Munich, School of Medicine and Health, German Heart Center, TUM University Hospital, Munich, Germany., Ligero M; Else Kroener Fresenius Center for Digital Health, Technical University Dresden, Dresden, Germany., Kühn JP; Institute and Polyclinic for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Carl Gustav Carus Dresden, Technical University Dresden, Dresden, Germany., Hoffmann RT; Institute and Polyclinic for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Carl Gustav Carus Dresden, Technical University Dresden, Dresden, Germany., Truhn D; Department of Diagnostic and Interventional Radiology, University Hospital Aachen, Aachen, Germany., Kather JN; Else Kroener Fresenius Center for Digital Health, Technical University Dresden, Dresden, Germany. kather.jn@tu-dresden.de.; Department of Medicine I, Faculty of Medicine and University Hospital Carl Gustav Carus, Technical University Dresden, Dresden, Germany. kather.jn@tu-dresden.de.; Medical Oncology, National Center for Tumor Diseases (NCT), University Hospital Heidelberg, Heidelberg, Germany. kather.jn@tu-dresden.de.; Pathology & Data Analytics, Leeds Institute of Medical Research at St James's, University of Leeds, Leeds, UK. kather.jn@tu-dresden.de.
Source: BMC medical imaging [BMC Med Imaging] 2026 Jan 08; Vol. 26 (1), pp. 54. Date of Electronic Publication: 2026 Jan 08.
Publication Type: Journal Article
Journal Info: Publisher: BioMed Central Country of Publication: England NLM ID: 100968553 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-2342 (Electronic) Linking ISSN: 14712342 NLM ISO Abbreviation: BMC Med Imaging Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1471-2342
DOI:10.1186/s12880-025-02075-4