Anand P. Santhanam, Michael Lauria, Brad Stiehl, Daniel Elliott, Saty Seshan, Scott Hsieh, Minsong Cao, Daniel Low. An adversarial machine-learning-based approach and biomechanically guided validation for improving deformable image registration accuracy between a planning CT and cone-beam CT for adaptive prostate radiotherapy applications. In Ivana Isgum, Bennett A. Landman, editors, Medical Imaging 2020: Image Processing, SPIE MEDICAL IMAGING, Houston, TX, USA, February 15-20, 2020. Volume 11313 of SPIE Proceedings, SPIE, 2020. [doi]
@inproceedings{SanthanamLSESHC20,
title = {An adversarial machine-learning-based approach and biomechanically guided validation for improving deformable image registration accuracy between a planning CT and cone-beam CT for adaptive prostate radiotherapy applications},
author = {Anand P. Santhanam and Michael Lauria and Brad Stiehl and Daniel Elliott and Saty Seshan and Scott Hsieh and Minsong Cao and Daniel Low},
year = {2020},
doi = {10.1117/12.2550493},
url = {https://doi.org/10.1117/12.2550493},
researchr = {https://researchr.org/publication/SanthanamLSESHC20},
cites = {0},
citedby = {0},
booktitle = {Medical Imaging 2020: Image Processing, SPIE MEDICAL IMAGING, Houston, TX, USA, February 15-20, 2020},
editor = {Ivana Isgum and Bennett A. Landman},
volume = {11313},
series = {SPIE Proceedings},
publisher = {SPIE},
isbn = {9781510633933},
}