Deep learning-based reconstruction and superresolution for MR-guided thermal ablation of malignant liver lesions.

Journal: Cancer imaging : the official publication of the International Cancer Imaging Society
PMID: 40176185

Abstract

OBJECTIVE: This study evaluates the impact of deep learning-enhanced T1-weighted VIBE sequences (DL-VIBE) on image quality and procedural parameters during MR-guided thermoablation of liver malignancies, compared to standard VIBE (SD-VIBE).

Authors

  • Moritz T Winkelmann
    Department of Radiology, Diagnostic and Interventional Radiology, University of Tübingen, 72076, Tübingen, Germany.
  • Jens Kübler
    Department of Radiology, Diagnostic and Interventional Radiology, University of Tübingen, 72076 Germany.
  • Sebastian Gassenmaier
    Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA.
  • Dominik M Nickel
    MR Application Predevelopment, Siemens Healthcare AG, Forchheim, Germany.
  • Antonia Ashkar
    Department of Diagnostic and Interventional Radiology, University Hospital of Tübingen, Hoppe-Seyler-Straße 3, 72076, Tübingen, Germany.
  • Konstantin Nikolaou
    Department of Diagnostic and Interventional Radiology, Eberhard-Karls-University, Hoppe-Seyler-Str.3, 72076 Tübingen, Germany.
  • Saif Afat
    Department of Diagnostic and Interventional Radiology, Eberhard-Karls-University Tuebingen, Tuebingen, Germany.
  • Rüdiger Hoffmann
    From the Department of Diagnostic and Interventional Radiology, Eberhard Karls University, Tuebingen University Hospital, Tuebingen.

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