Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Andreas Smolders"'
Autor:
Nermin Morgan, Adriaan Van Gerven, Andreas Smolders, Karla de Faria Vasconcelos, Holger Willems, Reinhilde Jacobs
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-9 (2022)
Abstract An accurate three-dimensional (3D) segmentation of the maxillary sinus is crucial for multiple diagnostic and treatment applications. Yet, it is challenging and time-consuming when manually performed on a cone-beam computed tomography (CBCT)
Externí odkaz:
https://doaj.org/article/99d2d32e203d4892b4e92122f40555ad
Autor:
Andreas Smolders, Adriaan C. Hengeveld, Stefan Both, Robin Wijsman, Johannes A. Langendijk, Damien C. Weber, Anthony J. Lomax, Francesca Albertini, Gabriel Guterres Marmitt
Publikováno v:
Radiotherapy & Oncology, 182
Smolders, A; Hengeveld, A C; Both, S; Wijsman, R; Langendijk, J A; Weber, D C; Lomax, T; Albertini, F; Guterres Marmitt, G (2023). Inter-and intrafractional 4D dose accumulation for evaluating ΔNTCP robustness in lung cancer. Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology, 182(109488), p. 109488. Elsevier Scientific Publ. Ireland 10.1016/j.radonc.2023.109488
Smolders, A; Hengeveld, A C; Both, S; Wijsman, R; Langendijk, J A; Weber, D C; Lomax, T; Albertini, F; Guterres Marmitt, G (2023). Inter-and intrafractional 4D dose accumulation for evaluating ΔNTCP robustness in lung cancer. Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology, 182(109488), p. 109488. Elsevier Scientific Publ. Ireland 10.1016/j.radonc.2023.109488
Background and purpose: Model-based selection of proton therapy patients relies on a predefined reduction in normal tissue complication probability (NTCP) with respect to photon therapy. The decision is necessarily made based on the treatment plan, b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6435f99873256f368760fd2664a6891a
https://hdl.handle.net/20.500.11850/598937
https://hdl.handle.net/20.500.11850/598937
Autor:
Khalid Ayidh Alqahtani, Reinhilde Jacobs, Andreas Smolders, Adriaan Van Gerven, Holger Willems, Sohaib Shujaat, Eman Shaheen
Publikováno v:
European journal of orthodontics.
Summary Objective Tooth segmentation and classification from cone-beam computed tomography (CBCT) is a prerequisite for diagnosis and treatment planning in the majority of digital dental workflows. However, an accurate and efficient segmentation of t
Autor:
Flavia Preda, Nermin Morgan, Adriaan Van Gerven, Fernanda Nogueira-Reis, Andreas Smolders, Xiaotong Wang, Stefanos Nomidis, Eman Shaheen, Holger Willems, Reinhilde Jacobs
Publikováno v:
Journal of dentistry. 124
The present study investigated the accuracy, consistency, and time-efficiency of a novel deep convolutional neural network (CNN) based model for the automated maxillofacial bone segmentation from cone beam computed tomography (CBCT) images.A dataset
Autor:
Maurício do Nascimento Gerhardt, Rocharles Cavalcante Fontenele, André Ferreira Leite, Pierre Lahoud, Adriaan Van Gerven, Holger Willems, Andreas Smolders, Thomas Beznik, Reinhilde Jacobs
Publikováno v:
Journal of dentistry. 122
To assess the accuracy of a novel Artificial Intelligence (AI)-driven tool for automated detection of teeth and small edentulous regions on Cone-Beam Computed Tomography (CBCT) images.After AI training and testing with 175 CBCT scans (130 for trainin
Autor:
Nermin Morgan, Adriaan Van Gerven, Andreas Smolders, Karla de Faria Vasconcelos, Holger Willems, Reinhilde Jacobs
Publikováno v:
Scientific reports. 12(1)
An accurate three-dimensional (3D) segmentation of the maxillary sinus is crucial for multiple diagnostic and treatment applications. Yet, it is challenging and time-consuming when manually performed on a cone-beam computed tomography (CBCT) dataset.
Autor:
Holger Willems, Adriaan Van Gerven, Andreas Smolders, Reinhilde Jacobs, Eman Shaheen, André Ferreira Leite, Khalid Alqahtani
Publikováno v:
Journal of dentistry. 115
Objectives Automatic tooth segmentation and classification from cone beam computed tomography (CBCT) have become an integral component of the digital dental workflows. Therefore, the aim of this study was to develop and validate a deep learning appro
Autor:
Eman Shaheen, Holger Willems, Jeroen Meewis, Adriaan Van Gerven, Pieter-Jan Verhelst, Andreas Smolders, Constantinus Politis, Arne Vandemeulebroucke, Reinhilde Jacobs, Thomas Beznik
Publikováno v:
Journal of Dentistry. 114:103786
OBJECTIVE: To develop and validate a layered deep learning algorithm which automatically creates three-dimensional (3D) surface models of the human mandible out of cone-beam computed tomography (CBCT) imaging. MATERIALS & METHODS: Two convolutional n