Fully automated spleen segmentation predicts progression-free survival in HCC patients following transarterial radioembolization.
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| Title: | Fully automated spleen segmentation predicts progression-free survival in HCC patients following transarterial radioembolization. |
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| Authors: | Steinhelfer L; Department of Diagnostic and Interventional Neuroradiology, Technical University of Munich, School of Medicine and Health, TUM University Hospital, Klinikum Rechts der Isar Ismaninger Str. 22, Munich, 81675, Germany. lisa.steinhelfer@tum.de.; Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany. lisa.steinhelfer@tum.de.; Department of Nuclear Medicine, Technical University of Munich, School of Medicine and Health, TUM University Hospital Munich, Munich, Germany. lisa.steinhelfer@tum.de., Jungmann F; Department of Radiology, Technical University of Munich, School of Medicine and Health, TUM University Hospital, Munich, Germany.; Chair for AI in Healthcare and Medicine, Technical University of Munich (TUM) and TUM University Hospital, Munich, Germany., Endroes L; Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany., Nickel M; Chair for AI in Healthcare and Medicine, Technical University of Munich (TUM) and TUM University Hospital, Munich, Germany., Schweizer N; Department of Radiology, Technical University of Munich, School of Medicine and Health, TUM University Hospital, Munich, Germany., Ehmer U; TUM School of Medicine and Health - Clinical Department of Internal Medicine II, TUM University Hospital, Munich, Germany.; Bavarian Cancer Research Center (BZKF), Erlangen, Germany.; German Cancer Consortium (DKTK), partner site Munich, a partnership between DKFZ and School of Medicine, Technical University of Munich, Munich, Germany., Haller B; Chair for AI in Healthcare and Medicine, Technical University of Munich (TUM) and TUM University Hospital, Munich, Germany., Walter R; Department of Radiology, Technical University of Munich, School of Medicine and Health, TUM University Hospital, Munich, Germany., Spaeth C; Department of Radiology, Technical University of Munich, School of Medicine and Health, TUM University Hospital, Munich, Germany., Einwächter H; TUM School of Medicine and Health - Clinical Department of Internal Medicine II, TUM University Hospital, Munich, Germany., Bodden J; Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany., Knorr K; Department of Nuclear Medicine, Technical University of Munich, School of Medicine and Health, TUM University Hospital Munich, Munich, Germany., Eiber M; Department of Nuclear Medicine, Technical University of Munich, School of Medicine and Health, TUM University Hospital Munich, Munich, Germany.; Bavarian Cancer Research Center (BZKF), Erlangen, Germany., Braren R; Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.; Department of Radiology, Technical University of Munich, School of Medicine and Health, TUM University Hospital, Munich, Germany.; German Cancer Consortium (DKTK), partner site Munich, a partnership between DKFZ and School of Medicine, Technical University of Munich, Munich, Germany. |
| Source: | European journal of nuclear medicine and molecular imaging [Eur J Nucl Med Mol Imaging] 2026 May; Vol. 53 (6), pp. 3904-3914. Date of Electronic Publication: 2026 Feb 17. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Springer-Verlag Berlin Country of Publication: Germany NLM ID: 101140988 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1619-7089 (Electronic) Linking ISSN: 16197070 NLM ISO Abbreviation: Eur J Nucl Med Mol Imaging Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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