A quantitative prediction of the post-operative lobectomy lung physiology using a GPU-based linear elastic lung biomechanics model and a constrained generative adversarial learning approach

Anand P. Santhanam, Brad Stiehl, Michael Lauria, Igor Barjaktarevic, Jonathan G. Goldin, Jane Yanagawa, Daniel Low. A quantitative prediction of the post-operative lobectomy lung physiology using a GPU-based linear elastic lung biomechanics model and a constrained generative adversarial learning approach. In Cristian A. Linte, Jeffrey H. Siewerdsen, editors, Medical Imaging 2021: Image-Guided Procedures, Robotic Interventions, and Modeling, Online, February 15-20, 2021. Volume 11598 of SPIE Proceedings, SPIE, 2021. [doi]

@inproceedings{SanthanamSLBGYL21,
  title = {A quantitative prediction of the post-operative lobectomy lung physiology using a GPU-based linear elastic lung biomechanics model and a constrained generative adversarial learning approach},
  author = {Anand P. Santhanam and Brad Stiehl and Michael Lauria and Igor Barjaktarevic and Jonathan G. Goldin and Jane Yanagawa and Daniel Low},
  year = {2021},
  doi = {10.1117/12.2582271},
  url = {https://doi.org/10.1117/12.2582271},
  researchr = {https://researchr.org/publication/SanthanamSLBGYL21},
  cites = {0},
  citedby = {0},
  booktitle = {Medical Imaging 2021: Image-Guided Procedures, Robotic Interventions, and Modeling, Online, February 15-20, 2021},
  editor = {Cristian A. Linte and Jeffrey H. Siewerdsen},
  volume = {11598},
  series = {SPIE Proceedings},
  publisher = {SPIE},
  isbn = {9781510640269},
}