AIMC Topic: Anatomic Landmarks
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Artificial intelligence to automate assessment of ocular and periocular measurements.
European journal of ophthalmology
May 6, 2024
PURPOSE: To develop and validate a deep learning facial landmark detection network to automate the assessment of periocular anthropometric measurements.
Deep learning for automatic detection of cephalometric landmarks on lateral cephalometric radiographs using the Mask Region-based Convolutional Neural Network: a pilot study.
Oral surgery, oral medicine, oral pathology and oral radiology
Feb 12, 2024
OBJECTIVE: We examined the effectiveness and feasibility of the Mask Region-based Convolutional Neural Network (Mask R-CNN) for automatic detection of cephalometric landmarks on lateral cephalometric radiographs (LCRs).
Knee landmarks detection via deep learning for automatic imaging evaluation of trochlear dysplasia and patellar height.
European radiology
Feb 10, 2024
OBJECTIVES: To develop and validate a deep learning-based approach to automatically measure the patellofemoral instability (PFI) indices related to patellar height and trochlear dysplasia in knee magnetic resonance imaging (MRI) scans.
Accuracy of artificial intelligence-assisted growth prediction in skeletal Class I preadolescent patients using serial lateral cephalograms for a 2-year growth interval.
Orthodontics & craniofacial research
Feb 6, 2024
OBJECTIVE: To investigate the accuracy of artificial intelligence-assisted growth prediction using a convolutional neural network (CNN) algorithm and longitudinal lateral cephalograms (Lat-cephs).
Applications of artificial intelligence in dentomaxillofacial imaging: a systematic review.
Oral surgery, oral medicine, oral pathology and oral radiology
Jan 3, 2024
BACKGROUND: Artificial intelligence (AI) technology has been increasingly developed in oral and maxillofacial imaging. The aim of this systematic review was to assess the applications and performance of the developed algorithms in different dentomaxi...
LOW CERTAINTY OF EVIDENCE SUPPORTS THE APPLICATION OF (AI) FOR THE AUTOMATIC DETECTION OF CEPHALOMETRIC LANDMARKS WITH PROSPECTS FOR IMPROVEMENTS.
The journal of evidence-based dental practice
Dec 21, 2023
ARTICLE TITLE AND BIBLIOGRAPHIC INFORMATION: Artificial Intelligence for Detecting Cephalometric Landmarks: A Systematic Review and Meta-analysis. J Digit Imaging. 2023 Jun;36(3):1158-1179. doi:10.1007/s10278-022-00766-w.
An artificial intelligence study: automatic description of anatomic landmarks on panoramic radiographs in the pediatric population.
BMC oral health
Oct 17, 2023
BACKGROUND: Panoramic radiographs, in which anatomic landmarks can be observed, are used to detect cases closely related to pediatric dentistry. The purpose of the study is to investigate the success and reliability of the detection of maxillary and ...
Deep Learning for the Assessment of Facial Nerve Palsy: Opportunities and Challenges.
Facial plastic surgery : FPS
Jun 8, 2023
Automated evaluation of facial palsy using machine learning offers a promising solution to the limitations of current assessment methods, which can be time-consuming, labor-intensive, and subject to clinician bias. Deep learning-driven systems have t...
Accuracy of automated 3D cephalometric landmarks by deep learning algorithms: systematic review and meta-analysis.
La Radiologia medica
Apr 24, 2023
OBJECTIVES: The aim of the present systematic review and meta-analysis is to assess the accuracy of automated landmarking using deep learning in comparison with manual tracing for cephalometric analysis of 3D medical images.
Evaluation of an artificial intelligence-based algorithm for automated localization of craniofacial landmarks.
Clinical oral investigations
Apr 4, 2023
OBJECTIVES: Due to advancing digitalisation, it is of interest to develop standardised and reproducible fully automated analysis methods of cranial structures in order to reduce the workload in diagnosis and treatment planning and to generate objecti...
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