Cone‐beam CT‐derived relative stopping power map generation via deep learning for proton radiotherapy
Medical Physics2020Vol. 47(9), pp. 4416–4427
Citations Over TimeTop 10% of 2020 papers
Joseph Harms, Yang Lei, Tonghe Wang, Mark W. McDonald, Beth Ghavidel, William A. Stokes, Walter J. Curran, Jun Zhou, Tian Liu, Xiaofeng Yang
Abstract
The proposed method provides sufficiently accurate RSP map generation from CBCT images, allowing for evaluation of daily dose based on CBCT and possibly allowing for CBCT-guided adaptive treatment planning for IMPT.
Related Papers
- → 211 Clinical introduction of image-guided radiotherapy, IGRT with Cone Beam CT(2005)3 cited
- → Evaluation of image guided radiotherapy (IGRT) in lung cancer. Is weekly cone beam CT (CBCT) enough?(2015)1 cited
- → 2013 POSTER Is the Contouring of Regions of Interest on Cone-beam CT Performed During IGRT Reliable Enough for Adaptive Radiotherapy?(2011)
- → PO-0666: Evaluation of image guided radiotherapy (IGRT) in lung cancer. Is weekly cone beam CT (CBCT) enough?(2015)
- → 109 poster workshop Automatic prostate localization for high precision image-guided radiotherapy (IGRT)First results using cone-beam CT (CBCT) scans(2004)