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Coen Hurkmans

Showing results (1-10 of 63) with videos related to

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Radiotherapy and Oncology : Journal of the European Society for Therapeutic Radiology and Oncology|March 11, 2020
Generalizability assessment of head and neck cancer NTCP models based on the TRIPOD criteriaMarjan Sharabiani, Enrico Clementel, Nicolaus Andratschke, et al.
Radiotherapy and Oncology : Journal of the European Society for Therapeutic Radiology and Oncology|January 22, 2008
Significance of breast boost volume changes during radiotherapy in relation to current clinical interobserver variationsCoen Hurkmans, Marjan Admiraal, Maurice van der Sangen, et al.
Physics and Imaging in Radiation Oncology|December 16, 2025
Statistical process control for performance monitoring and continuous quality assurance of deep learning segmentations in radiotherapyNiels van Acht, Dave van Gruijthuijsen, Johanna Bluemink, et al.
Acta Oncologica (Stockholm, Sweden)|June 20, 2024
Comparison of the use of a clinically implemented deep learning segmentation model with the simulated study setting for breast cancer patients receiving radiotherapyNienke Bakx, Maurice Van der Sangen, Jacqueline Theuws, et al.
Technical Innovations & Patient Support in Radiation Oncology|May 22, 2023
Comparison of the output of a deep learning segmentation model for locoregional breast cancer radiotherapy trained on 2 different datasetsNienke Bakx, Maurice van der Sangen, Jacqueline Theuws, et al.
Physics and Imaging in Radiation Oncology|October 4, 2023
Evaluation of a clinically introduced deep learning model for radiotherapy treatment planning of breast cancerNienke Bakx, Maurice van der Sangen, Jacqueline Theuws, et al.
Physics and Imaging in Radiation Oncology|February 2, 2024
Knowledge-based versus deep learning based treatment planning for breast radiotherapyDaniel Portik, Enrico Clementel, Jérôme Krayenbühl, et al.
Physics and Imaging in Radiation Oncology|April 26, 2021
Development and evaluation of radiotherapy deep learning dose prediction models for breast cancerNienke Bakx, Hanneke Bluemink, Els Hagelaar, et al.
Physics and Imaging in Radiation Oncology|April 20, 2026
Automated deep learning segmentation and planning for left-sided breast radiotherapy with minimised adaptations based on dose, TCP and NTCP criteriaNiels van Acht, Andreea Ciobotaru, Maurice van der Sangen, et al.
BJR Artificial Intelligence|May 1, 2026
Clinical adoption of deep learning target auto-segmentation for radiation therapy: challenges, clinical risks, and mitigation strategiesAlessia De Biase, Nanna Maria Sijtsema, Tomas Janssen, et al.
Pageof 7

Showing results (1-10 of 63) with videos related to

Sort By:
Pageof 7
Radiotherapy and Oncology : Journal of the European Society for Therapeutic Radiology and Oncology|March 11, 2020
Generalizability assessment of head and neck cancer NTCP models based on the TRIPOD criteriaMarjan Sharabiani, Enrico Clementel, Nicolaus Andratschke, et al.
Radiotherapy and Oncology : Journal of the European Society for Therapeutic Radiology and Oncology|January 22, 2008
Significance of breast boost volume changes during radiotherapy in relation to current clinical interobserver variationsCoen Hurkmans, Marjan Admiraal, Maurice van der Sangen, et al.
Physics and Imaging in Radiation Oncology|December 16, 2025
Statistical process control for performance monitoring and continuous quality assurance of deep learning segmentations in radiotherapyNiels van Acht, Dave van Gruijthuijsen, Johanna Bluemink, et al.
Acta Oncologica (Stockholm, Sweden)|June 20, 2024
Comparison of the use of a clinically implemented deep learning segmentation model with the simulated study setting for breast cancer patients receiving radiotherapyNienke Bakx, Maurice Van der Sangen, Jacqueline Theuws, et al.
Technical Innovations & Patient Support in Radiation Oncology|May 22, 2023
Comparison of the output of a deep learning segmentation model for locoregional breast cancer radiotherapy trained on 2 different datasetsNienke Bakx, Maurice van der Sangen, Jacqueline Theuws, et al.
Physics and Imaging in Radiation Oncology|October 4, 2023
Evaluation of a clinically introduced deep learning model for radiotherapy treatment planning of breast cancerNienke Bakx, Maurice van der Sangen, Jacqueline Theuws, et al.
Physics and Imaging in Radiation Oncology|February 2, 2024
Knowledge-based versus deep learning based treatment planning for breast radiotherapyDaniel Portik, Enrico Clementel, Jérôme Krayenbühl, et al.
Physics and Imaging in Radiation Oncology|April 26, 2021
Development and evaluation of radiotherapy deep learning dose prediction models for breast cancerNienke Bakx, Hanneke Bluemink, Els Hagelaar, et al.
Physics and Imaging in Radiation Oncology|April 20, 2026
Automated deep learning segmentation and planning for left-sided breast radiotherapy with minimised adaptations based on dose, TCP and NTCP criteriaNiels van Acht, Andreea Ciobotaru, Maurice van der Sangen, et al.
BJR Artificial Intelligence|May 1, 2026
Clinical adoption of deep learning target auto-segmentation for radiation therapy: challenges, clinical risks, and mitigation strategiesAlessia De Biase, Nanna Maria Sijtsema, Tomas Janssen, et al.
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