Maskless 2-dimensional digital subtraction angiography generation model for abdominal vasculature using deep learning

HIGHLIGHTS

• who: Hiroki Yonezawa MD from the This retrospective study was approved by the Ethical Committee of Osaka City University Graduate School of MedicineBecause the images were acquired during daily clinical practice, the need for informed consent was waived. This study followed the Checklist for Artificial Intelligence in Medical Imaging and Standards for Reporting Diagnostic Accuracy statements (11, ). First, native angiograms and , DSA images were retrospectively collected. The DL model was trained and tuned with pairs of native angiograms and , DSA images without motion artifacts. The have published the research: Maskless 2-Dimensional Digital Subtraction Angiography Generation Model . . .
  

   

  

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