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 …
Quality assurance based on deep learning for pelvic OARs delineation in radiotherapy
H Yu, Y He, Y Fu, X Li, J Zhang… - Current Medical Imaging, 2023 - ingentaconnect.com
Background: Correct delineation of organs at risk (OARs) is an important step for
radiotherapy and it is also a time-consuming process that depends on many factors …
radiotherapy and it is also a time-consuming process that depends on many factors …
Explaining the dosimetric impact of contouring errors in head and neck radiotherapy
PJ González, R Simões, K Kiers… - Biomedical Physics & …, 2022 - iopscience.iop.org
Objective. Auto-contouring of organs at risk (OAR) is becoming more common in
radiotherapy. An important issue in clinical decision making is judging the quality of the auto …
radiotherapy. An important issue in clinical decision making is judging the quality of the auto …
[PDF][PDF] Towards the Automatic Discovery of Rules Based on ECG Data for the Support of Personalized Medical Decisions
M Zouri - 2022 - rshare.library.torontomu.ca
Understanding the complexity of heart diseases is considerably important in early detection
and developing personalized, highly effective therapies. However, the high number of …
and developing personalized, highly effective therapies. However, the high number of …
[引用][C] 726: Weakly supervised commissioning of externally developed auto-segmentation models
BWK Schipaanboord, PJ Koopmans… - Radiotherapy and …, 2024 - Elsevier