Multi-criteria optimization and decision-making in radiotherapy

S Breedveld, D Craft, R Van Haveren… - European Journal of …, 2019 - Elsevier
Radiotherapy (radiation therapy) is one of the main treatments for cancer. The aim is to
deliver a prescribed radiation dose to the tumor, while kee** the unavoidable dose to the …

A feasibility study for predicting optimal radiation therapy dose distributions of prostate cancer patients from patient anatomy using deep learning

D Nguyen, T Long, X Jia, W Lu, X Gu, Z Iqbal… - Scientific reports, 2019 - nature.com
With the advancement of treatment modalities in radiation therapy for cancer patients,
outcomes have improved, but at the cost of increased treatment plan complexity and …

Incorporating human and learned domain knowledge into training deep neural networks: a differentiable dose‐volume histogram and adversarial inspired framework …

D Nguyen, R McBeth… - Medical …, 2020 - Wiley Online Library
Purpose We propose a novel domain‐specific loss, which is a differentiable loss function
based on the dose‐volume histogram (DVH), and combine it with an adversarial loss for the …

DeepMC: a deep learning method for efficient Monte Carlo beamlet dose calculation by predictive denoising in magnetic resonance-guided radiotherapy

R Neph, Q Lyu, Y Huang, YM Yang… - Physics in Medicine & …, 2021 - iopscience.iop.org
Emerging magnetic resonance (MR) guided radiotherapy affords significantly improved
anatomy visualization and, subsequently, more effective personalized treatment. The new …

Complexity in radiation therapy: it's complicated

E Kamperis, C Kodona, K Hatziioannou… - International Journal of …, 2020 - redjournal.org
The culmination of radiation therapy's technical innovation during the past few decades led
to the development of volumetric modulated arc therapy (VMAT), 1 which constitutes the …

A novel optimization framework for VMAT with dynamic gantry couch rotation

Q Lyu, YY Victoria, D Ruan, R Neph… - Physics in Medicine …, 2018 - iopscience.iop.org
Existing volumetric modulated arc therapy (VMAT) optimization using coplanar arcs is highly
efficient but usually dosimetrically inferior to intensity modulated radiation therapy (IMRT) …

Tomographic detection of photon pairs produced from high-energy X-rays for the monitoring of radiotherapy dosing

Q Lyu, R Neph, K Sheng - Nature Biomedical Engineering, 2023 - nature.com
Measuring the radiation dose reaching a patient's body is difficult. Here we report a
technique for the tomographic reconstruction of the location of photon pairs originating from …

Using deep learning to predict beam‐tunable Pareto optimal dose distribution for intensity‐modulated radiation therapy

G Bohara, A Sadeghnejad Barkousaraie… - Medical …, 2020 - Wiley Online Library
Purpose Many researchers have developed deep learning models for predicting clinical
dose distributions and Pareto optimal dose distributions. Models for predicting Pareto …

Fraction-variant beam orientation optimization for non-coplanar IMRT

D O'Connor, V Yu, D Nguyen, D Ruan… - Physics in Medicine & …, 2018 - iopscience.iop.org
Conventional beam orientation optimization (BOO) algorithms for IMRT assume that the
same set of beam angles is used for all treatment fractions. In this paper we present a BOO …

A hybrid meta-heuristic framework with ensemble deep learning for multi-functional simultaneous optimized automatic intensity-modulated radiotherapy planning

X Yang, S Li, Q Shao, D Tang, Z Peng, Y Cao… - Expert Systems with …, 2025 - Elsevier
Intensity-modulated radiotherapy (IMRT) is one of the main treatments for patients with
cancer, and its treatment planning holds significant importance. Compared to manual …