Deep learning stopping power maps supported magnetic resonance-only proton planning for brain tumors
Synthetic stopping power maps showed small target dose differences, but residual range and low-dose gamma errors still require further validation.
Tag
deep-learning
Multimodal respiratory tracking enabled real-time voxel-wise anatomical reconstruction during radiotherapy
The patient-specific framework outperformed three comparison methods and reconstructed respiratory anatomy in 15.6 milliseconds per frame.
Virtual contrast-enhanced MRI matched gadolinium-enhanced imaging for diagnosis, staging, and tumor delineation.
98.98% of virtual contrast-enhanced MRI scans were rated suitable for diagnosis, and 92.33% for tumor delineation.
Physics-constrained network improved cone-beam computed tomography reconstruction from orthogonal pelvic radiographs
A physics-constrained network reconstructed pelvic cone-beam computed tomography from two simulated radiographs with substantially lower error than generative baselines.