AIMC Topic: Cone-Beam Computed Tomography
Clear Filters Showing 401 to 410 of 432 articles
Adolescents and Children Age Estimation Using Machine Learning Based on Pulp and Tooth Volumes on CBCT Images.
Fa yi xue za zhi
Apr 25, 2024
OBJECTIVES: To estimate adolescents and children age using stepwise regression and machine learning methods based on the pulp and tooth volumes of the left maxillary central incisor and cuspid on cone beam computed tomography (CBCT) images, and to co...
Dental Artificial Intelligence Systems: A Review of Various Data Types.
Discovery medicine
Mar 1, 2024
With the rapid development of dental artificial intelligence systems (DAIS), a new field known as "Data Dentistry", proposed by Schwendicke in 2021, has successfully bridged the gap between medicine and engineering. This literature review introduces ...
A content-aware chatbot based on GPT 4 provides trustworthy recommendations for Cone-Beam CT guidelines in dental imaging.
Dento maxillo facial radiology
Feb 8, 2024
OBJECTIVES: To develop a content-aware chatbot based on GPT-3.5-Turbo and GPT-4 with specialized knowledge on the German S2 Cone-Beam CT (CBCT) dental imaging guideline and to compare the performance against humans.
Machine learning assessment of dental age classification based on cone-beam CT images: a different approach.
Dento maxillo facial radiology
Jan 11, 2024
OBJECTIVES: Machine learning (ML) algorithms are a portion of artificial intelligence that may be used to create more accurate algorithmic procedures for estimating an individual's dental age or defining an age classification. This study aims to use ...
[Mitigating metal artifacts from cobalt-chromium alloy crowns in cone-beam CT images through deep learning techniques].
Zhonghua kou qiang yi xue za zhi = Zhonghua kouqiang yixue zazhi = Chinese journal of stomatology
Jan 9, 2024
To develop and evaluate metal artifact removal systems (MARS) based on deep learning to assess their effectiveness in removing artifacts caused by different thicknesses of metals in cone-beam CT (CBCT) images. A full-mouth standard model (60 mm×75 ...
Artificial intelligence versus semi-automatic segmentation of the inferior alveolar canal on cone-beam computed tomography scans: A pilot study.
Dental and medical problems
Jan 1, 2024
BACKGROUND: The inferior alveolar canal (IAC) is a fundamental mandibular structure. It is important to conduct a precise pre-surgical evaluation of the IAC to prevent complications. Recently, the use of artificial intelligence (AI) has demonstrated ...
Are multi-detector computed tomography and cone-beam computed tomography exams and software accurate to measure the upper airway? A systematic review.
European journal of orthodontics
Nov 30, 2023
BACKGROUND: Cone-beam computed tomography (CBCT) has several applications in various fields of dental medicine such as diagnosis and treatment planning. When compared to computed tomography (CT), CBCT's radiation exposure dose is decreased by 3%-20%....
Musculoskeletal CT Imaging: State-of-the-Art Advancements and Future Directions.
Radiology
Aug 1, 2023
CT is one of the most widely used modalities for musculoskeletal imaging. Recent advancements in the field include the introduction of four-dimensional CT, which captures a CT image during motion; cone-beam CT, which uses flat-panel detectors to capt...
[Research on multi-class orthodontic image recognition system based on deep learning network model].
Zhonghua kou qiang yi xue za zhi = Zhonghua kouqiang yixue zazhi = Chinese journal of stomatology
Jun 9, 2023
To develop a multi-classification orthodontic image recognition system using the SqueezeNet deep learning model for automatic classification of orthodontic image data. A total of 35 000 clinical orthodontic images were collected in the Department o...
Automatic detection of adenoid hypertrophy on cone-beam computed tomography based on deep learning.
American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics
Apr 1, 2023
INTRODUCTION: This study proposed an automatic diagnosis method based on deep learning for adenoid hypertrophy detection on cone-beam computed tomography.
Stay Ahead of Medical AI
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 31059
- Neural Networks, Computer 29727
- Algorithms 26848
- Deep Learning 26366
- Artificial Intelligence 24311
- Robotics 13314
- Image Processing, Computer-Assisted 9527
- Retrospective Studies 9114
- Magnetic Resonance Imaging 6186
- Reproducibility of Results 5593
- Tomography, X-Ray Computed 4772
- Support Vector Machine 4688
- Computational Biology 4240
- Brain 4053
- Computer Simulation 3882
Recent Journals
- Scientific reports 5971
- Sensors (Basel, Switzerland) 4794
- PloS one 4022
- Neural networks : the official journal of the International Neural Network Society 2930
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1860
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1278
- IEEE journal of biomedical and health informatics 1131
- Journal of chemical information and modeling 1000
- Nature communications 949
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 861
- Briefings in bioinformatics 853
- IEEE transactions on neural networks and learning systems 826