STATEMENT OF PROBLEM: Zygomatic implants (ZIs) should be placed accurately as planned preoperatively to minimize complications and maximize the use of the remaining bone. Current digital techniques such as static guides and dynamic navigation are aff...
OBJECTIVE(S): This study aims to evaluate the influence of the piezocision surgery in the orthodontic biomechanics, as well as in the magnitude and direction of tooth movement in the mandibular arch using novel artificial intelligence (AI)-automated ...
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Nov 27, 2023
PURPOSE: The use of iterative and deep learning reconstruction methods, which would allow effective noise reduction, is limited in cone-beam computed tomography (CBCT). As a consequence, the visibility of soft tissues is limited with CBCT. The study ...
OBJECTIVES: In interventional bronchial artery embolization (BAE), periprocedural cone beam CT (CBCT) improves guiding and localization. However, a trade-off exists between 6-second runs (high radiation dose and motion artifacts, but low noise) and 3...
INTRODUCTION: Training of Artificial Intelligence (AI) for biomedical image analysis depends on large annotated datasets. This study assessed the efficacy of Active Learning (AL) strategies training AI models for accurate multilabel segmentation and ...
Forensic science, medicine, and pathology
Nov 16, 2023
Human or time resources can sometimes fall short in medical image diagnostics, and analyzing images in full detail can be a challenging task. With recent advances in artificial intelligence, an increasing number of systems have been developed to assi...
BACKGROUND: One of the limitations in leveraging the potential of artificial intelligence in X-ray imaging is the limited availability of annotated training data. As X-ray and CT shares similar imaging physics, one could achieve cross-domain data sha...
OBJECTIVES: This study aimed to investigate the accuracy of deep learning algorithms to diagnose tooth caries and classify the extension and location of dental caries in cone beam computed tomography (CBCT) images. To the best of our knowledge, this ...
The objective of this study is to use a deep-learning model based on CNN architecture to detect the second mesiobuccal (MB2) canals, which are seen as a variation in maxillary molars root canals. In the current study, 922 axial sections from 153 pati...
OBJECTIVE: To compare a three-dimensional (3D) artificial intelligence (AI)- driven model with panoramic radiography (PANO) and cone-beam computed tomography (CBCT) in assessing the risk of inferior alveolar nerve (IAN) injury after mandibular wisdom...
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