Mapping the Use of Artificial Intelligence–Based Image Analysis for Clinical Decision‐Making in Dentistry: A Scoping Review

W Chen, M Dhawan, J Liu, D Ing… - Clinical and …, 2024 - Wiley Online Library
Objectives Artificial intelligence (AI) is an emerging field in dentistry. AI is gradually being
integrated into dentistry to improve clinical dental practice. The aims of this scoping review …

Dose prescription for stereotactic body radiotherapy: general and organ-specific consensus statement from the DEGRO/DGMP Working Group Stereotactic …

TB Brunner, J Boda-Heggemann, D Bürgy… - Strahlentherapie und …, 2024 - Springer
Purpose and objective To develop expert consensus statements on multiparametric dose
prescriptions for stereotactic body radiotherapy (SBRT) aligning with ICRU report 91. These …

Multi-organ segmentation of abdominal structures from non-contrast and contrast enhanced CT images

C Yu, CP Anakwenze, Y Zhao, RM Martin, EB Ludmir… - Scientific reports, 2022 - nature.com
Manually delineating upper abdominal organs at risk (OARs) is a time-consuming task. To
develop a deep-learning-based tool for accurate and robust auto-segmentation of these …

Automatic contouring QA method using a deep learning–based autocontouring system

DJ Rhee, CPA Akinfenwa, B Rigaud… - Journal of applied …, 2022 - Wiley Online Library
Purpose To determine the most accurate similarity metric when using an independent
system to verify automatically generated contours. Methods A reference autocontouring …

Target definition in MR-guided adaptive radiotherapy for head and neck cancer

M Ridder, CPJ Raaijmakers, FA Pameijer, R Bree… - Cancers, 2022 - mdpi.com
Simple Summary Adaptive radiotherapy for head and neck cancer has become more routine
due to an increase in imaging quality and improvement in radiation techniques. With the …

Accuracy of the doses computed by the Eclipse treatment planning system near and inside metal elements

B Pawałowski, A Ryczkowski, R Panek… - Scientific reports, 2022 - nature.com
Metal artefacts degrade clinical image quality which decreases the confidence of using
computed tomography (CT) for the delineation of key structures for treatment planning and …

Graph-based motion artifacts detection method from head computed tomography images

Y Liu, T Wen, W Sun, Z Liu, X Song, X He, S Zhang… - Sensors, 2022 - mdpi.com
Computed tomography (CT) images play an important role due to effectiveness and
accessibility, however, motion artifacts may obscure or simulate pathology and dramatically …

Comprehensive quantitative evaluation of variability in magnetic resonance-guided delineation of oropharyngeal gross tumor volumes and high-risk clinical target …

CE Cardenas, SE Blinde, ASR Mohamed, SP Ng… - International Journal of …, 2022 - Elsevier
Purpose Tumor and target volume manual delineation remains a challenging task in head
and neck cancer radiation therapy. The purpose of this study was to conduct a multi …

Motion Artifact Detection Based on Regional–Temporal Graph Attention Network from Head Computed Tomography Images

Y Liu, T Wen, Z Wu - Electronics, 2024 - mdpi.com
Artifacts are the main cause of degradation in CT image quality and diagnostic accuracy.
Because of the complex texture of CT images, it is a challenging task to automatically detect …