Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Filters

Ward van Rooij

Showing results (1-10 of 6) with videos related to

Pageof 1
Sort By:
Advances in Radiation Oncology|March 29, 2021
Using Spatial Probability Maps to Highlight Potential Inaccuracies in Deep Learning-Based Contours: Facilitating Online Adaptive Radiation TherapyWard van Rooij, Wilko F Verbakel, Berend J Slotman, et al.
Radiation Oncology (London, England)|December 2, 2020
Strategies to improve deep learning-based salivary gland segmentationWard van Rooij, Max Dahele, Hanne Nijhuis, et al.
Medical Physics|April 29, 2023
Impact of imperfection in medical imaging data on deep learning-based segmentation performance: An experimental study using synthesized dataAyetullah Mehdi Güneş, Ward van Rooij, Sadaf Gulshad, et al.
International Journal of Radiation Oncology, Biology, Physics|March 6, 2019
Deep Learning-Based Delineation of Head and Neck Organs at Risk: Geometric and Dosimetric EvaluationWard van Rooij, Max Dahele, Hugo Ribeiro Brandao, et al.
Medical Physics|May 23, 2023
Deep learning-based markerless lung tumor tracking in stereotactic radiotherapy using Siamese networksDragos Grama, Max Dahele, Ward van Rooij, et al.
Acta Oncologica (Stockholm, Sweden)|January 11, 2021
Investigating the potential of deep learning for patient-specific quality assurance of salivary gland contours using EORTC-1219-DAHANCA-29 clinical trial dataHanne Nijhuis, Ward van Rooij, Vincent Gregoire, et al.
Pageof 1

Showing results (1-10 of 6) with videos related to

Sort By:
Pageof 1
Advances in Radiation Oncology|March 29, 2021
Using Spatial Probability Maps to Highlight Potential Inaccuracies in Deep Learning-Based Contours: Facilitating Online Adaptive Radiation TherapyWard van Rooij, Wilko F Verbakel, Berend J Slotman, et al.
Radiation Oncology (London, England)|December 2, 2020
Strategies to improve deep learning-based salivary gland segmentationWard van Rooij, Max Dahele, Hanne Nijhuis, et al.
Medical Physics|April 29, 2023
Impact of imperfection in medical imaging data on deep learning-based segmentation performance: An experimental study using synthesized dataAyetullah Mehdi Güneş, Ward van Rooij, Sadaf Gulshad, et al.
International Journal of Radiation Oncology, Biology, Physics|March 6, 2019
Deep Learning-Based Delineation of Head and Neck Organs at Risk: Geometric and Dosimetric EvaluationWard van Rooij, Max Dahele, Hugo Ribeiro Brandao, et al.
Medical Physics|May 23, 2023
Deep learning-based markerless lung tumor tracking in stereotactic radiotherapy using Siamese networksDragos Grama, Max Dahele, Ward van Rooij, et al.
Acta Oncologica (Stockholm, Sweden)|January 11, 2021
Investigating the potential of deep learning for patient-specific quality assurance of salivary gland contours using EORTC-1219-DAHANCA-29 clinical trial dataHanne Nijhuis, Ward van Rooij, Vincent Gregoire, et al.
Pageof 1