AIMC Topic: Cone-Beam Computed Tomography
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Evaluation of the effectiveness of panoramic radiography in impacted mandibular third molars on deep learning models developed with findings obtained with cone beam computed tomography.
Oral radiology
Dec 27, 2024
OBJECTIVE: The aim of this study is to determine the contact relationship and position of impacted mandibular third molar teeth (IMM) with the mandibular canal (MC) in panoramic radiography (PR) images using deep learning (DL) models trained with the...
Fast motion-compensated reconstruction for 4D-CBCT using deep learning-based groupwise registration.
Biomedical physics & engineering express
Dec 23, 2024
. Previous work has that deep learning (DL)-enhanced 4D cone beam computed tomography (4D-CBCT) images improve motion modeling and subsequent motion-compensated (MoCo) reconstruction for 4D-CBCT. However, building the motion model at treatment time v...
Deep learning and radiomics-based vascular calcification characterization in dental cone beam computed tomography as a predictive tool for cardiovascular disease: a proof-of-concept study.
Oral surgery, oral medicine, oral pathology and oral radiology
Dec 18, 2024
OBJECTIVES: This study evaluated an automated deep learning method for detecting calcifications in the extracranial and intracranial carotid arteries and vertebral arteries in cone beam computed tomography (CBCT) scans. Additionally, a model utilizin...
Automated Segmentation of Graft Material in 1-Stage Sinus Lift Based on Artificial Intelligence: A Retrospective Study.
Clinical implant dentistry and related research
Dec 16, 2024
OBJECTIVES: Accurate assessment of postoperative bone graft material changes after the 1-stage sinus lift is crucial for evaluating long-term implant survival. However, traditional manual labeling and segmentation of cone-beam computed tomography (CB...
Unsupervised Bayesian generation of synthetic CT from CBCT using patient-specific score-based prior.
Medical physics
Dec 12, 2024
BACKGROUND: Cone-beam computed tomography (CBCT) scans, performed fractionally (e.g., daily or weekly), are widely utilized for patient alignment in the image-guided radiotherapy (IGRT) process, thereby making it a potential imaging modality for the ...
Artificial Intelligence-Assisted Segmentation of a Falx Cerebri Calcification on Cone-Beam Computed Tomography: A Case Report.
Medicina (Kaunas, Lithuania)
Dec 12, 2024
Intracranial calcifications, particularly within the falx cerebri, serve as crucial diagnostic markers ranging from benign accumulations to signs of severe pathologies. The falx cerebri, a dural fold that separates the cerebral hemispheres, presents ...
Evaluation of the mandibular canal and the third mandibular molar relationship by CBCT with a deep learning approach.
Oral radiology
Dec 11, 2024
OBJECTIVE: The mandibular canal (MC) houses the inferior alveolar nerve. Extraction of the mandibular third molar (MM3) is a common dental surgery, often complicated by nerve damage. CBCT is the most effective imaging method to assess the relationshi...
A novel AI model for detecting periapical lesion on CBCT: CBCT-SAM.
Journal of dentistry
Dec 10, 2024
OBJECTIVES: Periapical lesions are not always evident on radiographic scans. Sometimes, asymptomatic or initial periapical lesions on cone-beam computed tomography (CBCT) could be missed by inexperienced dentists, especially when the scan has a large...
Application of task-autonomous dental robot for lateral window preparation in the maxillary sinus.
Journal of cranio-maxillo-facial surgery : official publication of the European Association for Cranio-Maxillo-Facial Surgery
Dec 6, 2024
The study aimed to investigate the feasibility and accuracy of task-autonomous dental robots for lateral window preparation in the maxillary sinus, as well as to propose 3 indexes for assessing the accuracy of lateral window preparation. Twenty 1:1 r...
Detection of three-rooted mandibular first molars on panoramic radiographs using deep learning.
Scientific reports
Dec 5, 2024
This study aimed to develop a deep learning system for the detection of three-rooted mandibular first molars (MFMs) on panoramic radiographs and to assess its diagnostic performance. Panoramic radiographs, together with cone beam computed tomographic...
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