A5082520902- Cleft Lip and Palate Research
- Craniofacial Disorders and Treatments
- Anatomy and Medical Technology
- Surgical Simulation and Training
- Dental Radiography and Imaging
- Augmented Reality Applications
- Orthodontics and Dentofacial Orthopedics
- Forensic Anthropology and Bioarchaeology Studies
- Intracranial Aneurysms: Treatment and Complications
- dental development and anomalies
- Traumatic Brain Injury and Neurovascular Disturbances
- Facial Trauma and Fracture Management
- AI in cancer detection
- Medical and Biological Sciences
- Vascular Malformations Diagnosis and Treatment
- Morphological variations and asymmetry
- Aortic aneurysm repair treatments
- Transcranial Magnetic Stimulation Studies
- Fetal and Pediatric Neurological Disorders
- Medical Imaging and Analysis
- Prosthetics and Rehabilitation Robotics
- Facial Nerve Paralysis Treatment and Research
- Soft Robotics and Applications
- Pain Mechanisms and Treatments
- Cerebrovascular and Carotid Artery Diseases
Radboud University Nijmegen
2017-2024
Radboud University Medical Center
2017-2024
University Medical Center
2022-2024
Radboud Institute for Molecular Life Sciences
2024
University of Twente
2015
Abstract The approximity of the inferior alveolar nerve (IAN) to roots lower third molars (M3) is a risk factor for occurrence damage and subsequent sensory disturbances lip chin following removal molars. To assess this risk, identification M3 IAN on dental panoramic radiographs (OPG) mandatory. In study, we developed validated an automated approach, based deep-learning, detect segment OPGs. As reference, M3s were segmented manually 81 A deep-learning approach U-net was applied reference...
Neuroanatomy education is a challenging field which could benefit from modern innovations, such as augmented reality (AR) applications. This study investigates the differences on test scores, cognitive load, and motivation after neuroanatomy learning using AR applications or cross‐sections of brain. Prior to two practical assignments, pretest (extended matching questions, double‐choice questions cross‐sectional anatomy) mental rotation (MRT) were completed. Sex MRT scores used stratify...
Abstract BACKGROUND Predicting outcome after aneurysmal subarachnoid hemorrhage (aSAH) is known to be challenging and complex. Machine learning approaches, of which feedforward artificial neural networks (ffANNs) are the most widely used, could contribute patient-specific prediction. OBJECTIVE To investigate prediction capacity an ffANN for clinical occurrence delayed cerebral ischemia (DCI) compare those results with predictions 2 internationally used scoring systems. METHODS A prospective...
The study aimed at developing a deep-learning (DL)-based algorithm to predict the virtual soft tissue profile after mandibular advancement surgery, and compare its accuracy with mass tensor model (MTM). Subjects who underwent surgery were enrolled divided into training group test group. DL was trained using 3D photographs CBCT data based on surgically achieved displacements (training group). Soft simulations generated by MTM actual surgical jaw movements (test group) compared soft-tissue...
Abstract Craniosynostosis is a condition in which cranial sutures fuse prematurely, causing problems normal brain and skull growth infants. To limit the extent of cosmetic functional problems, swift diagnosis needed. The goal this study to investigate if deep learning algorithm capable correctly classifying head shape infants as either healthy controls, or one following three craniosynostosis subtypes; scaphocephaly, trigonocephaly anterior plagiocephaly. In order acquire data, 3D...
Abstract Although an increased usage and development of 3D technologies is observed in healthcare over the last decades, full integration these remains challenging. The goal this project to qualitatively explore challenges, pearls, pitfalls AR/VR/3D printing applications medical field a university center. Two rounds face-to-face interviews were conducted using semi-structured protocol. First explorative round was held, interviewing specialists (8), PhD students (7), technology (5), teachers...
Abstract Three-dimensional facial stereophotogrammetry provides a detailed representation of craniofacial soft tissue without the use ionizing radiation. While manual annotation landmarks serves as current gold standard for cephalometric analysis, it is time-consuming process and prone to human error. The aim in this study was develop evaluate an automated method using deep learning-based approach. Ten were manually annotated on 2897 3D photographs. landmarking workflow involved two...
Neuroanatomy as a subject is important to learn, because good understanding of neuroanatomy supports the establishment correct diagnosis in neurological patients. However, rapid changes curricula reduced time assigned study (neuro)anatomy. Therefore, it find alternative teaching methods complex three-dimensional structure brain. The aim this manuscript was explore effectiveness Virtual Reality (VR) comparison with Radiological Data (RaD) suitable learning build knowledge and increase...
In order to assess the severity and progression of a unilateral peripheral facial palsy Sunnybrook Facial Grading System (SFGS) is well-established grading system due its clinical relevance, sensitivity, robust measuring method. However, training required in achieve high inter-rater reliability. This study investigated automated patients based on SFGS using convolutional neural network.A total 116 with 9 healthy subjects were recorded performing poses. A separate model was trained for each...
Computer-assisted technologies have made significant progress in fetoscopic laser surgery, including placental vessel segmentation. However, the intra- and inter-procedure variabilities state-of-the-art segmentation methods remain a hurdle. To address this, we investigated use of conditional generative adversarial networks (cGANs) for image compared their performance with benchmark U-Net technique Two deep-learning models, pix2pix (a popular cGAN model), were trained evaluated using publicly...
The available reference data for the mandible and mandibular growth consists primarily of two-dimensional linear or angular measurements. aim this study was to create first open-source, three-dimensional statistical shape model that spans complete period. Computed tomography scans 678 mandibles from children young adults between 0 22 years old were included in model. segmented using a semi-automatic automatic (artificial intelligence-based) segmentation method. Point correspondence among...
The publication rate of neurosurgical guidelines has increased tremendously over the past decade; however, only a small proportion clinical decisions appear to be based on high-quality evidence.
The use of augmented reality (AR) in teaching and studying neuroanatomy has been well researched. Previous research showed that AR-based learning both alleviated cognitive load was attractive to young learners. However, how the attractiveness AR effects student motivation not discovered. Therefore, motivational were investigated this by quantitative qualitative methods. Motivation elicited GreyMapp-AR, an application, medical biomedical sciences students (n = 222; mean age: 19.7 ± 1.4 years)...
Summary Background: This retrospective cohort study evaluated the longitudinal three-dimensional (3D) cranial shape developments and secondary treatment aspects after endoscopically assisted craniosynostosis surgery (EACS) with helmet therapy open vault reconstruction (OCVR) for scaphocephaly. Methods: Longitudinally collected 3D photos from scaphocephaly patients healthy infants were evaluated. measurements growth maps compared between groups over time. Secondary groups. Results: Both...
Virtual planning of open cranial vault reconstruction is used to simulate and define an pre-operative plan for craniosynostosis surgery. However, virtual techniques are subjective dependent on the experience preferences surgical team. To develop objective automated 3D technique reconstructions, we curvature maps shape comparison patient's skull with age-specific reference skull. We created average age-group 11-14 months. Also, artificial test object selected a CT-scan 11 months old...