ArticleRadiology. Artificial intelligence2020
A Vertebral Segmentation Dataset with Fracture Grading.
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Article in Radiology. Artificial intelligence, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers.
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57citing papers in PubMed
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Who cites it
57 citing papers in PubMed.
- VERIDAH: solving enumeration anomaly-aware vertebra labeling across imaging sequences.European radiology · 2026Article
- Diagnostic accuracy of deep learning vs. human raters for detecting osteoporotic vertebral compression fractures in routine CT scans.European radiology · 2026Article
- Fully Automated Segmentation of Anatomical Subregions of the Thoracolumbar Spine on Computed Tomography.Journal of imaging informatics in medicine · 2026Article
- Investigating robot control policy learning for autonomous x-ray-guided spine procedures.International journal of computer assisted radiology and surgery · 2026Article
- Design of 3D-printed hydroxyapatite intervertebral fusion cages in a patient specific framework.Medical & biological engineering & computing · 2026Article
- Article
- A large, paired dataset of robotic and handheld lumbar spine ultrasound with ground-truth CT benchmarking.Scientific data · 2025Article
- Article
- Attention LinkNet-152: a novel encoder-decoder based deep learning network for automated spine segmentation.Scientific reports · 2025Article
- A novel dual-branch segmentation algorithm for overall spine segmentation.Quantitative imaging in medicine and surgery · 2025Article
- Evaluating Skellytour for Automated Skeleton Segmentation from Whole-Body CT Images.Radiology. Artificial intelligence · 2025Article
- An Intrinsically Explainable Approach to Detecting Vertebral Compression Fractures in CT Scans via Neurosymbolic Modeling.Proceedings of SPIE--the International Society for Optical Engineering · 2025Article
- Enhanced Detection Performance of Acute Vertebral Compression Fractures Using a Hybrid Deep Learning and Traditional Quantitative Measurement Approach: Beyond the Limitations of Genant Classification.Bioengineering (Basel, Switzerland) · 2025Article
- Article
- Thoracic vertebral bone mineral density measured by quantitative computed tomography is associated with fracture risk in lung cancer screening populations: a prospective cohort study.Frontiers in endocrinology · 2025Article
- Enhanced nnU-Net Architectures for Automated MRI Segmentation of Head and Neck Tumors in Adaptive Radiation Therapy.Head and Neck Tumor Segmentation for MR-Guided Applications : First MICCAI Challenge, HNTS-MRG 2024, held in conjunction with MICCAI 2024, Marrakesh, Morocco, October 17, 2024, proceedings · 2025Article
- GeoCrack: A High-Resolution Dataset For Segmentation of Fracture Edges in Geological Outcrops.Scientific data · 2024Article
- An open annotated dataset and baseline machine learning model for segmentation of vertebrae with metastatic bone lesions from CT.medRxiv : the preprint server for health sciences · 2024Article
- Improved Detection Accuracy of Chronic Vertebral Compression Fractures by Integrating Height Loss Ratio and Deep Learning Approaches.Diagnostics (Basel, Switzerland) · 2024Article
- Automated deep learning-based bone mineral density assessment for opportunistic osteoporosis screening using various CT protocols with multi-vendor scanners.Scientific reports · 2024Article
Corrections and comments
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Authors and funding
10 authors.
Maximilian T LöfflerDepartment of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Ismaninger Str 22, Munich 81675, Germany (M.T.L., A. Sekuboyina, A.J., A.L.G., A. Scharr, M.E.H., M.K., C.Z., T.B., J.S.K.); and Department of Informatics, Technical University of Munich, Munich, Germany (A. Sekuboyina).ORCID 0000-0002-6022-3682
Anjany SekuboyinaDepartment of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Ismaninger Str 22, Munich 81675, Germany (M.T.L., A. Sekuboyina, A.J., A.L.G., A. Scharr, M.E.H., M.K., C.Z., T.B., J.S.K.); and Department of Informatics, Technical University of Munich, Munich, Germany (A. Sekuboyina).ORCID 0000-0002-5601-284X
Alina JacobDepartment of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Ismaninger Str 22, Munich 81675, Germany (M.T.L., A. Sekuboyina, A.J., A.L.G., A. Scharr, M.E.H., M.K., C.Z., T.B., J.S.K.); and Department of Informatics, Technical University of Munich, Munich, Germany (A. Sekuboyina).
Anna-Lena GrauDepartment of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Ismaninger Str 22, Munich 81675, Germany (M.T.L., A. Sekuboyina, A.J., A.L.G., A. Scharr, M.E.H., M.K., C.Z., T.B., J.S.K.); and Department of Informatics, Technical University of Munich, Munich, Germany (A. Sekuboyina).ORCID 0000-0002-5659-4296
Andreas ScharrDepartment of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Ismaninger Str 22, Munich 81675, Germany (M.T.L., A. Sekuboyina, A.J., A.L.G., A. Scharr, M.E.H., M.K., C.Z., T.B., J.S.K.); and Department of Informatics, Technical University of Munich, Munich, Germany (A. Sekuboyina).ORCID 0000-0001-7900-3519
Malek El HusseiniDepartment of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Ismaninger Str 22, Munich 81675, Germany (M.T.L., A. Sekuboyina, A.J., A.L.G., A. Scharr, M.E.H., M.K., C.Z., T.B., J.S.K.); and Department of Informatics, Technical University of Munich, Munich, Germany (A. Sekuboyina).
Mareike KallweitDepartment of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Ismaninger Str 22, Munich 81675, Germany (M.T.L., A. Sekuboyina, A.J., A.L.G., A. Scharr, M.E.H., M.K., C.Z., T.B., J.S.K.); and Department of Informatics, Technical University of Munich, Munich, Germany (A. Sekuboyina).
Claus ZimmerDepartment of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Ismaninger Str 22, Munich 81675, Germany (M.T.L., A. Sekuboyina, A.J., A.L.G., A. Scharr, M.E.H., M.K., C.Z., T.B., J.S.K.); and Department of Informatics, Technical University of Munich, Munich, Germany (A. Sekuboyina).
Thomas BaumDepartment of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Ismaninger Str 22, Munich 81675, Germany (M.T.L., A. Sekuboyina, A.J., A.L.G., A. Scharr, M.E.H., M.K., C.Z., T.B., J.S.K.); and Department of Informatics, Technical University of Munich, Munich, Germany (A. Sekuboyina).
Jan S KirschkeDepartment of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Ismaninger Str 22, Munich 81675, Germany (M.T.L., A. Sekuboyina, A.J., A.L.G., A. Scharr, M.E.H., M.K., C.Z., T.B., J.S.K.); and Department of Informatics, Technical University of Munich, Munich, Germany (A. Sekuboyina).ORCID 0000-0002-7557-0003
Funding
European Research Council 637164
Abstract
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