Generative adversarial networks in medical image segmentation: A review

S Xun, D Li, H Zhu, M Chen, J Wang, J Li… - Computers in biology …, 2022 - Elsevier
Abstract Purpose Since Generative Adversarial Network (GAN) was introduced into the field
of deep learning in 2014, it has received extensive attention from academia and industry …

[HTML][HTML] A review of the metrics used to assess auto-contouring systems in radiotherapy

K Mackay, D Bernstein, B Glocker, K Kamnitsas… - Clinical Oncology, 2023 - Elsevier
Auto-contouring could revolutionise future planning of radiotherapy treatment. The lack of
consensus on how to assess and validate auto-contouring systems currently limits clinical …

CBCT-guided adaptive radiotherapy using self-supervised sequential domain adaptation with uncertainty estimation

N Ebadi, R Li, A Das, A Roy, P Nikos, P Najafirad - Medical Image Analysis, 2023 - Elsevier
Adaptive radiotherapy (ART) is an advanced technology in modern cancer treatment that
incorporates progressive changes in patient anatomy into active plan/dose adaption during …

[HTML][HTML] The use of MR-guided radiation therapy for head and neck cancer and recommended reporting guidance

BA McDonald, R Dal Bello, CD Fuller… - Seminars in radiation …, 2024 - Elsevier
Although magnetic resonance imaging (MRI) has become standard diagnostic workup for
head and neck malignancies and is currently recommended by most radiological societies …

Automated delineation of head and neck organs at risk using synthetic MRI‐aided mask scoring regional convolutional neural network

X Dai, Y Lei, T Wang, J Zhou, J Roper… - Medical …, 2021 - Wiley Online Library
Purpose Auto‐segmentation algorithms offer a potential solution to eliminate the labor‐
intensive, time‐consuming, and observer‐dependent manual delineation of organs‐at‐risk …

[HTML][HTML] Artificial intelligence in image-guided radiotherapy: a review of treatment target localization

W Zhao, L Shen, MT Islam, W Qin, Z Zhang… - … Imaging in Medicine …, 2021 - ncbi.nlm.nih.gov
Modern conformal beam delivery techniques require image-guidance to ensure the
prescribed dose to be delivered as planned. Recent advances in artificial intelligence (AI) …

Multi-organ auto-delineation in head-and-neck MRI for radiation therapy using regional convolutional neural network

X Dai, Y Lei, T Wang, J Zhou, S Rudra… - Physics in Medicine …, 2022 - iopscience.iop.org
Magnetic resonance imaging (MRI) allows accurate and reliable organ delineation for many
disease sites in radiation therapy because MRI is able to offer superb soft-tissue contrast …

Synthetic CT‐aided multiorgan segmentation for CBCT‐guided adaptive pancreatic radiotherapy

X Dai, Y Lei, J Wynne, J Janopaul‐Naylor… - Medical …, 2021 - Wiley Online Library
Purpose The delineation of organs at risk (OARs) is fundamental to cone‐beam CT (CBCT)‐
based adaptive radiotherapy treatment planning, but is time consuming, labor intensive, and …

[HTML][HTML] Synthetic CT generation from cone-beam CT using deep-learning for breast adaptive radiotherapy

X Wang, W Jian, B Zhang, L Zhu, Q He, H **… - Journal of Radiation …, 2022 - Elsevier
We investigated the feasibility of the generation of synthetic CT (sCT) from CBCT images
with deep learning and the dose evaluation for CBCT-guided breast cancer adaptive …

Geometric and dosimetric evaluation of deep learning-based automatic delineation on CBCT-synthesized CT and planning CT for breast cancer adaptive radiotherapy …

Z Dai, Y Zhang, L Zhu, J Tan, G Yang, B Zhang… - Frontiers in …, 2021 - frontiersin.org
Purpose We developed a deep learning model to achieve automatic multitarget delineation
on planning CT (pCT) and synthetic CT (sCT) images generated from cone-beam CT …