Reinforcement learning optimizes adaptive angle selection and dose allocation in sparse-view CT reconstruction, yielding better quality and defect detectability than uniform strategies under limited projections or dose.
Penalized weighted least-squares approach to sinogram noise reduction and image reconstruction for low- dose x-ray computed tomography
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Deep Reinforcement Learning for Optimizing Angle Selection and Dose Allocation in CT Reconstruction
Reinforcement learning optimizes adaptive angle selection and dose allocation in sparse-view CT reconstruction, yielding better quality and defect detectability than uniform strategies under limited projections or dose.