Automatic Segmentation of Multi-center Multi-field-strength Perfusion CMR Datasets with Deep Learning-based Uncertainty-guided Analysis: Preliminary Findings Using the SCMR Registry

Lignende værker

• Automatic Segmentation of Multi-center Multi-field-strength Perfusion CMR Datasets with Deep Learning-based Uncertainty-guided Analysis: Preliminary Findings Using the SCMR Registry
  af: Dilek M. Yalcinkaya, MSc, et al.
  Udgivet: (2024-01-01)
• Reducing the Contrast Dose by 80% in Quantitative Perfusion CMR Enabled by Patch-wise Deep Learning
  af: Khalid Youssef, PhD, et al.
  Udgivet: (2024-01-01)
• Automatic Assessment of Tetralogy of Fallot CMR Reports FBom the SCMR Registry: Pre- and Post-pulmonary Valve Replacement
  af: Avan Suinesiaputra, PhD, et al.
  Udgivet: (2024-01-01)
• FBee-breathing, Ecg-FBee, Myocardial T1-T2 Joint Mapping in Healthy Subjects and Cardiomyopathy Patients
  af: Xianglun Mao, PhD, et al.
  Udgivet: (2024-01-01)
• Retrospective Phase-map Synthesis for CMR Datasets FBom Magnitude-only DICOM Images Enabled by A.I. Generative Models to Create Large Training Datasets for Deep Learning-based Image Reconstruction
  af: M. Berk Sahin, BSc, et al.
  Udgivet: (2024-01-01)