Radiomics and machine learning in oral healthcare
AF Leite, KF Vasconcelos, H Willems… - PROTEOMICS …, 2020 - Wiley Online Library
The increasing storage of information, data, and forms of knowledge has led to the
development of new technologies that can help to accomplish complex tasks in different …
development of new technologies that can help to accomplish complex tasks in different …
Deep learning methods for enhancing cone‐beam CT image quality toward adaptive radiation therapy: A systematic review
B Rusanov, GM Hassan, M Reynolds, M Sabet… - Medical …, 2022 - Wiley Online Library
The use of deep learning (DL) to improve cone‐beam CT (CBCT) image quality has gained
popularity as computational resources and algorithmic sophistication have advanced in …
popularity as computational resources and algorithmic sophistication have advanced in …
Improving CBCT quality to CT level using deep learning with generative adversarial network
Purpose To improve image quality and computed tomography (CT) number accuracy of
daily cone beam CT (CBCT) through a deep learning methodology with generative …
daily cone beam CT (CBCT) through a deep learning methodology with generative …
Evaluation of a cycle-generative adversarial network-based cone-beam CT to synthetic CT conversion algorithm for adaptive radiation therapy
M Eckl, L Hoppen, GR Sarria, J Boda-Heggemann… - Physica Medica, 2020 - Elsevier
Purpose Image-guided radiation therapy could benefit from implementing adaptive radiation
therapy (ART) techniques. A cycle-generative adversarial network (cycle-GAN)-based cone …
therapy (ART) techniques. A cycle-generative adversarial network (cycle-GAN)-based cone …
The future of computed tomography: personalized, functional, and precise
Modern medicine cannot be imagined without the diagnostic capabilities of computed
tomography (CT). Although the past decade witnessed a tremendous increase in scan …
tomography (CT). Although the past decade witnessed a tremendous increase in scan …
Artificial intelligence for Monte Carlo simulation in medical physics
Monte Carlo simulation of particle tracking in matter is the reference simulation method in
the field of medical physics. It is heavily used in various applications such as 1) patient dose …
the field of medical physics. It is heavily used in various applications such as 1) patient dose …
Synthetic dual-energy CT for MRI-only based proton therapy treatment planning using label-GAN
MRI-only treatment planning is highly desirable in the current proton radiation therapy
workflow due to its appealing advantages such as bypassing MR-CT co-registration …
workflow due to its appealing advantages such as bypassing MR-CT co-registration …
An unsupervised dual contrastive learning framework for scatter correction in cone-beam CT image
Purpose: Cone-beam computed tomography (CBCT) is widely utilized in modern
radiotherapy; however, CBCT images exhibit increased scatter artifacts compared to …
radiotherapy; however, CBCT images exhibit increased scatter artifacts compared to …
A more effective CT synthesizer using transformers for cone-beam CT-guided adaptive radiotherapy
X Chen, Y Liu, B Yang, J Zhu, S Yuan, X Xie… - Frontiers in …, 2022 - frontiersin.org
Purpose The challenge of cone-beam computed tomography (CBCT) is its low image
quality, which limits its application for adaptive radiotherapy (ART). Despite recent …
quality, which limits its application for adaptive radiotherapy (ART). Despite recent …
Artificial intelligence in radiotherapy: a technological review
K Sheng - Frontiers of Medicine, 2020 - Springer
Radiation therapy (RT) is widely used to treat cancer. Technological advances in RT have
occurred in the past 30 years. These advances, such as three-dimensional image guidance …
occurred in the past 30 years. These advances, such as three-dimensional image guidance …