Artificial intelligence in radiation oncology

E Huynh, A Hosny, C Guthier, DS Bitterman… - Nature Reviews …, 2020 - nature.com
Artificial intelligence (AI) has the potential to fundamentally alter the way medicine is
practised. AI platforms excel in recognizing complex patterns in medical data and provide a …

Knowledge‐based planning for intensity‐modulated radiation therapy: a review of data‐driven approaches

Y Ge, QJ Wu - Medical physics, 2019 - Wiley Online Library
Purpose Intensity‐Modulated Radiation Therapy (IMRT), including its variations (including
IMRT, Volumetric Arc Therapy (VMAT), and Tomotherapy), is a widely used and critically …

Artificial intelligence in clinical applications for lung cancer: diagnosis, treatment and prognosis

Q Pei, Y Luo, Y Chen, J Li, D Xie, T Ye - Clinical Chemistry and …, 2022 - degruyter.com
Artificial intelligence (AI) is a branch of computer science that includes research in robotics,
language recognition, image recognition, natural language processing, and expert systems …

Radiation therapy quality assurance tasks and tools: the many roles of machine learning

AM Kalet, SMH Luk, MH Phillips - Medical physics, 2020 - Wiley Online Library
The recent explosion in machine learning efforts in the quality assurance (QA) space has
produced a variety of proofs‐of‐concept many with promising results. Expected outcomes of …

Using artificial intelligence for optimization of the processes and resource utilization in radiotherapy

R Krishnamurthy, N Mummudi, JS Goda… - JCO Global …, 2022 - ascopubs.org
The radiotherapy (RT) process from planning to treatment delivery is a multistep, complex
operation involving numerous levels of human-machine interaction and requiring high …

Channel-wise attention enhanced and structural similarity constrained cycleGAN for effective synthetic CT generation from head and neck MRI images

C Gong, Y Huang, M Luo, S Cao, X Gong, S Ding… - Radiation …, 2024 - Springer
Background Magnetic resonance imaging (MRI) plays an increasingly important role in
radiotherapy, enhancing the accuracy of target and organs at risk delineation, but the …

Learning-based dose prediction for pancreatic stereotactic body radiation therapy using dual pyramid adversarial network

S Momin, Y Lei, T Wang, J Zhang… - Physics in Medicine …, 2021 - iopscience.iop.org
Abstract Treatment planning for pancreatic cancer stereotactic body radiation therapy
(SBRT) is very challenging owing to vast spatial variations and close proximity of many …

Convolutional neural network‐based dosimetry evaluation of esophageal radiation treatment planning

D Jiang, H Yan, N Chang, T Li, R Mao, C Du… - Medical …, 2020 - Wiley Online Library
Purpose A dosimetry evaluation model for treatment planning of esophageal radiation
therapy is developed using a deep learning model. The model predicts dose volume …

A medical expert system approach using artificial neural networks for standardized treatment planning

DM Wells, J Niederer - International Journal of Radiation Oncology* Biology …, 1998 - Elsevier
Purpose: Many radiotherapy treatment plans involve some level of standardization (eg, in
terms of beam ballistics, collimator settings, and wedge angles), which is determined …

Prism: a new approach to radiotherapy planning software.

IJ Kalet, JP Jacky, MM Austin-Seymour… - … journal of radiation …, 1996 - europepmc.org
Purpose We describe the capabilities and performance of Prism, an innovative new
radiotherapy planning system with unusual features and design. The design and …