papersTODAY 04:00 UTC
Reinforcement Learning Optimizes CT Protocols via Virtual Imaging Trials
Researchers apply reinforcement learning to CT protocol tuning, where acquisition and reconstruction settings interact in ways that make brute-force testing impractical. Their framework relies on virtual imaging trials to search the parameter space and balance diagnostic image quality against radiation exposure. The work appears as a cross-listed arXiv submission in machine learning.
arXivct-protocol-optimizationmedical imagingradiation-dose-reductionreinforcement-learningvirtual-imaging-trials
COVERAGE · 2 REPORTS · LINKS GO TO THE ORIGINAL OUTLETS
arXiv cs.AITask-Based CT Protocol Optimization Using Reinforcement Learning and Virtual Imaging Trials ↗TODAY 04:00 UTC
arXiv cs.LGTask-Based CT Protocol Optimization Using Reinforcement Learning and Virtual Imaging Trials ↗TODAY 04:00 UTC