Using Deep Learning to Predict Beam-Tunable Pareto Optimal Dose Distribution for Intensity Modulated Radiation Therapy

Lignende værker

• Incorporating human and learned domain knowledge into training deep neural networks: A differentiable dose volume histogram and adversarial inspired framework for generating Pareto optimal dose distributions in radiation therapy
  af: Nguyen, Dan, et al.
  Udgivet: (2019)
• A Fast Deep Learning Approach for Beam Orientation Optimization for Prostate Cancer Treated with Intensity Modulated Radiation Therapy
  af: Barkousaraie, Azar Sadeghnejad, et al.
  Udgivet: (2020)
• A physics-informed deep learning model for predicting beam dose distribution of intensity-modulated radiation therapy treatment plans
  af: Zihan Sun, et al.
  Udgivet: (2025-04-01)
• A feasibility study for predicting optimal radiation therapy dose distributions of prostate cancer patients from patient anatomy using deep learning
  af: Nguyen, Dan, et al.
  Udgivet: (2019)
• Evaluating the Therapeutic Dose Distribution of Intensity-Modulated Radiation Therapy for Head and Neck with Cone-Beam Computed Tomography Image: A Methodological Study
  af: Zhang, Guang-shun, et al.
  Udgivet: (2014)