HIGHLIGHTS
- who: Nika Guberina and collaborators from the University of Toronto, Canada have published the research work: Machine-learning-based prediction of the effectiveness of the delivered dose by exhale-gated radiotherapy for locally advanced lung cancer: The additional value of geometric over dosimetric parameters alone, in the Journal: (JOURNAL)
- what: The aim of this analysis is the characterization of the dosimetric and geometric parameters related to the residual deformations of the clinical target volume (CTV) in prefractional, exhale-gated CBCT scans after 6-degrees-offreedom image guidance. In this study, all deformed images and structures . . .
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