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

Adriaan Van Gerven

Showing results (1-10 of 14) with videos related to

Pageof 2
Sort By:
Journal of Dentistry|June 2, 2021
Automatic segmentation of the pharyngeal airway space with convolutional neural networkSohaib Shujaat, Omid Jazil, Holger Willems, et al.
Scientific Reports|May 7, 2022
Convolutional neural network for automatic maxillary sinus segmentation on cone-beam computed tomographic imagesNermin Morgan, Adriaan Van Gerven, Andreas Smolders, et al.
Journal of Endodontics|January 12, 2021
Artificial Intelligence for Fast and Accurate 3-Dimensional Tooth Segmentation on Cone-beam Computed TomographyPierre Lahoud, Mostafa EzEldeen, Thomas Beznik, et al.
International Journal of Environmental Research and Public Health|May 30, 2020
Artificial Intelligence (AI)-Driven Molar Angulation Measurements to Predict Third Molar Eruption on Panoramic RadiographsMyrthel Vranckx, Adriaan Van Gerven, Holger Willems, et al.
European Journal of Orthodontics|September 13, 2022
Deep convolutional neural network-based automated segmentation and classification of teeth with orthodontic brackets on cone-beam computed-tomographic images: a validation studyKhalid Ayidh Alqahtani, Reinhilde Jacobs, Andreas Smolders, et al.
Journal of Dentistry|October 28, 2021
A novel deep learning system for multi-class tooth segmentation and classification on cone beam computed tomography. A validation studyEman Shaheen, André Leite, Khalid Ayidh Alqahtani, et al.
Journal of Dentistry|November 15, 2021
Development and validation of a novel artificial intelligence driven tool for accurate mandibular canal segmentation on CBCTPierre Lahoud, Siebe Diels, Liselot Niclaes, et al.
Clinical Oral Investigations|August 27, 2020
Artificial intelligence-driven novel tool for tooth detection and segmentation on panoramic radiographsAndré Ferreira Leite, Adriaan Van Gerven, Holger Willems, et al.
Clinical Oral Investigations|September 17, 2022
Three-dimensional maxillary virtual patient creation by convolutional neural network-based segmentation on cone-beam computed tomography imagesFernanda Nogueira-Reis, Nermin Morgan, Stefanos Nomidis, et al.
Journal of Dentistry|February 20, 2022
Influence of dental fillings and tooth type on the performance of a novel artificial intelligence-driven tool for automatic tooth segmentation on CBCT images - A validation studyRocharles Cavalcante Fontenele, Maurício do Nascimento Gerhardt, Jáder Camilo Pinto, et al.
Pageof 2

Showing results (1-10 of 14) with videos related to

Sort By:
Pageof 2
Journal of Dentistry|June 2, 2021
Automatic segmentation of the pharyngeal airway space with convolutional neural networkSohaib Shujaat, Omid Jazil, Holger Willems, et al.
Scientific Reports|May 7, 2022
Convolutional neural network for automatic maxillary sinus segmentation on cone-beam computed tomographic imagesNermin Morgan, Adriaan Van Gerven, Andreas Smolders, et al.
Journal of Endodontics|January 12, 2021
Artificial Intelligence for Fast and Accurate 3-Dimensional Tooth Segmentation on Cone-beam Computed TomographyPierre Lahoud, Mostafa EzEldeen, Thomas Beznik, et al.
International Journal of Environmental Research and Public Health|May 30, 2020
Artificial Intelligence (AI)-Driven Molar Angulation Measurements to Predict Third Molar Eruption on Panoramic RadiographsMyrthel Vranckx, Adriaan Van Gerven, Holger Willems, et al.
European Journal of Orthodontics|September 13, 2022
Deep convolutional neural network-based automated segmentation and classification of teeth with orthodontic brackets on cone-beam computed-tomographic images: a validation studyKhalid Ayidh Alqahtani, Reinhilde Jacobs, Andreas Smolders, et al.
Journal of Dentistry|October 28, 2021
A novel deep learning system for multi-class tooth segmentation and classification on cone beam computed tomography. A validation studyEman Shaheen, André Leite, Khalid Ayidh Alqahtani, et al.
Journal of Dentistry|November 15, 2021
Development and validation of a novel artificial intelligence driven tool for accurate mandibular canal segmentation on CBCTPierre Lahoud, Siebe Diels, Liselot Niclaes, et al.
Clinical Oral Investigations|August 27, 2020
Artificial intelligence-driven novel tool for tooth detection and segmentation on panoramic radiographsAndré Ferreira Leite, Adriaan Van Gerven, Holger Willems, et al.
Clinical Oral Investigations|September 17, 2022
Three-dimensional maxillary virtual patient creation by convolutional neural network-based segmentation on cone-beam computed tomography imagesFernanda Nogueira-Reis, Nermin Morgan, Stefanos Nomidis, et al.
Journal of Dentistry|February 20, 2022
Influence of dental fillings and tooth type on the performance of a novel artificial intelligence-driven tool for automatic tooth segmentation on CBCT images - A validation studyRocharles Cavalcante Fontenele, Maurício do Nascimento Gerhardt, Jáder Camilo Pinto, et al.
Pageof 2