The Integration of Deep Learning in Radiotherapy: Exploring Challenges, Opportunities, and Future Directions through an Umbrella Review
A Lastrucci, Y Wandael, R Ricci, G Maccioni… - Diagnostics, 2024 - mdpi.com
This study investigates, through a narrative review, the transformative impact of deep
learning (DL) in the field of radiotherapy, particularly in light of the accelerated …
learning (DL) in the field of radiotherapy, particularly in light of the accelerated …
Artificial intelligence for treatment delivery: image-guided radiotherapy
Radiation therapy (RT) is a highly digitized field relying heavily on computational methods
and, as such, has a high affinity for the automation potential afforded by modern artificial …
and, as such, has a high affinity for the automation potential afforded by modern artificial …
Deep learning-based automatic contour quality assurance for auto-segmented abdominal MR-Linac contours
Objective. Deep-learning auto-segmentation (DLAS) aims to streamline contouring in
clinical settings. Nevertheless, achieving clinical acceptance of DLAS remains a hurdle in …
clinical settings. Nevertheless, achieving clinical acceptance of DLAS remains a hurdle in …
[HTML][HTML] Performance of Commercial Deep Learning-Based Auto-Segmentation Software for Breast Cancer Radiation Therapy Planning: A Systematic Review
CKC Ng - Multimodal Technologies and Interaction, 2024 - mdpi.com
As yet, no systematic review on commercial deep learning-based auto-segmentation (DLAS)
software for breast cancer radiation therapy (RT) planning has been published, although …
software for breast cancer radiation therapy (RT) planning has been published, although …
[HTML][HTML] Automated Organ Segmentation for Radiation Therapy: A Comparative Analysis of AI-Based Tools Versus Manual Contouring in Korean Cancer Patients
SH Choi, JW Park, Y Cho, G Yang, HI Yoon - Cancers, 2024 - mdpi.com
Background: Accurate delineation of tumors and organs at risk (OARs) is crucial for intensity-
modulated radiation therapy. This study aimed to evaluate the performance of OncoStudio …
modulated radiation therapy. This study aimed to evaluate the performance of OncoStudio …
How Italian radiation oncologists use ChatGPT: a survey by the young group of the Italian association of radiotherapy and clinical oncology (yAIRO)
A Piras, F Mastroleo, RR Colciago, I Morelli… - La radiologia …, 2024 - Springer
Purpose To investigate the awareness and the spread of ChatGPT and its possible role in
both scientific research and clinical practice among the young radiation oncologists (RO) …
both scientific research and clinical practice among the young radiation oncologists (RO) …
[HTML][HTML] Comparison of Vendor-Pretrained and Custom-Trained Deep Learning Segmentation Models for Head-and-Neck, Breast, and Prostate Cancers
X Chen, Y Zhao, H Baroudi, MD El Basha, A Daniel… - Diagnostics, 2024 - mdpi.com
Background/Objectives: We assessed the influence of local patients and clinical
characteristics on the performance of commercial deep learning (DL) segmentation models …
characteristics on the performance of commercial deep learning (DL) segmentation models …
Exploring the impact of field shape on predicted dose distribution in breast cancer patients using deep learning in radiation therapy
Background Geometrical information such as field shape is essential for dose calculation in
radiation therapy. However, new methods of dose prediction based on deep learning only …
radiation therapy. However, new methods of dose prediction based on deep learning only …
Cardiac substructure delineation in radiation therapy–A state‐of‐the‐art review
RN Finnegan, A Quinn, J Booth… - Journal of Medical …, 2024 - Wiley Online Library
Delineation of cardiac substructures is crucial for a better understanding of radiation‐related
cardiotoxicities and to facilitate accurate and precise cardiac dose calculation for developing …
cardiotoxicities and to facilitate accurate and precise cardiac dose calculation for developing …
U 型卷积网络在乳腺医学图像分割中的研究综述.
蒲秋梅， 殷帅， 李正茂， 赵丽娜 - Journal of Frontiers of …, 2024 - search.ebscohost.com
U-Net 及其变体模型在乳腺医学图像分割领域展现了卓越的性能, U-Net 采用全卷积网络(FCN)
结构进行语义分割, U-Net 对称结构的高度灵活性和适应性可以通过调整网络深度 …
结构进行语义分割, U-Net 对称结构的高度灵活性和适应性可以通过调整网络深度 …