Artificial intelligence in radiotherapy treatment planning: present and future

C Wang, X Zhu, JC Hong… - Technology in cancer …, 2019 - journals.sagepub.com
Treatment planning is an essential step of the radiotherapy workflow. It has become more
sophisticated over the past couple of decades with the help of computer science, enabling …

Automation in intensity modulated radiotherapy treatment planning—a review of recent innovations

M Hussein, BJM Heijmen, D Verellen… - The British journal of …, 2018 - academic.oup.com
Radiotherapy treatment planning of complex radiotherapy techniques, such as intensity
modulated radiotherapy and volumetric modulated arc therapy, is a resource-intensive …

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 …

3D radiotherapy dose prediction on head and neck cancer patients with a hierarchically densely connected U-net deep learning architecture

D Nguyen, X Jia, D Sher, MH Lin, Z Iqbal… - Physics in medicine …, 2019 - iopscience.iop.org
The treatment planning process for patients with head and neck (H&N) cancer is regarded
as one of the most complicated due to large target volume, multiple prescription dose levels …

DoseNet: a volumetric dose prediction algorithm using 3D fully-convolutional neural networks

V Kearney, JW Chan, S Haaf… - Physics in Medicine …, 2018 - iopscience.iop.org
The goal of this study is to demonstrate the feasibility of a novel fully-convolutional
volumetric dose prediction neural network (DoseNet) and test its performance on a cohort of …

Knowledge‐based radiation treatment planning: a data‐driven method survey

S Momin, Y Fu, Y Lei, J Roper… - Journal of applied …, 2021 - Wiley Online Library
This paper surveys the data‐driven dose prediction methods investigated for knowledge‐
based planning (KBP) in the last decade. These methods were classified into two major …

A transformer-embedded multi-task model for dose distribution prediction

L Wen, J **ao, S Tan, X Wu, J Zhou… - International Journal of …, 2023 - World Scientific
Radiation therapy is a fundamental cancer treatment in the clinic. However, to satisfy the
clinical requirements, radiologists have to iteratively adjust the radiotherapy plan based on …

MRI-based treatment planning for liver stereotactic body radiotherapy: validation of a deep learning-based synthetic CT generation method

Y Liu, Y Lei, T Wang, O Kayode, S Tian… - The British Journal of …, 2019 - academic.oup.com
Objective: The purpose of this work is to develop and validate a learning-based method to
derive electron density from routine anatomical MRI for potential MRI-based SBRT treatment …

Multi-level progressive transfer learning for cervical cancer dose prediction

L Wen, J **ao, J Zeng, C Zu, X Wu, J Zhou, X Peng… - Pattern Recognition, 2023 - Elsevier
Recently, deep learning has accomplished the automation of radiation therapy planning,
enhancing its quality and efficiency. However, such progress comes at the cost of a large …

Explainable attention guided adversarial deep network for 3D radiotherapy dose distribution prediction

H Li, X Peng, J Zeng, J **ao, D Nie, C Zu, X Wu… - Knowledge-Based …, 2022 - Elsevier
Radiotherapy is the mainstay treatment for most patients with cancer. During radiotherapy
planning, it is essential to generate a clinically acceptable dose distribution map. In practice …