AIMC Topic: Maxilla

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AI-Assisted 3D diagnosis of impacted maxillary canines: A validation study.

Clinical oral investigations
INTRODUCTION: This study aimed to validate an artificial intelligence (AI)-based automated image analysis for three-dimensional (3D) characterization of impacted canine position. In addition, it compared clinical treatment plans developed using conve...

Endodontic microsurgery utilizing an autonomous robotic system for the maxillary second molar: a case report.

BMC oral health
BACKGROUND: Endodontic microsurgery (EMS) is a widely utilized technique for addressing periapical periodontitis that is unresponsive to conventional root canal treatment. Nevertheless, achieving precise root apex location and resection can pose sign...

Enhanced diagnostic pipeline for maxillary sinus-maxillary molars relationships: a novel implementation of Detectron2 with faster R-CNN R50 FPN 3x on CBCT images.

BMC oral health
BACKGROUND: The anatomical relationship between the maxillary sinus and maxillary molars is critical for planning dental procedures such as tooth extraction, implant placement and periodontal surgery.

Evaluation of artificial intelligence-based cephalometric tracing versus semi-automatic and manual tracing.

BMC oral health
BACKGROUND: Artificial intelligence (AI)-based cephalometric tracing has emerged as a promising tool that reduces operator variability and offers standardized, rapid, and reproducible assessments. This study aimed to evaluate the reliability and accu...

Machine learning in sex estimation using CBCT morphometric measurements of canines.

Clinical oral investigations
OBJECTIVE: The aim of this study was to assess measurements of the maxillary canines using Cone Beam Computed Tomography (CBCT) and develop a machine learning model for sex estimation.

Predicting enamel depth distribution of maxillary teeth based on intraoral scanning: A machine learning study.

Journal of prosthodontic research
PURPOSE: Measuring enamel depth distribution (EDD) is of great importance for preoperative design of tooth preparations, restorative aesthetic preview and monitoring enamel wear. But, currently there are no non-invasive methods available to efficient...

The role of artificial intelligence in intraoral scanning for complete-arch digital impressions: An in vitro study.

Journal of dentistry
OBJECTIVES: Artificial intelligence (AI) is increasingly being integrated into intraoral scanners (IOS) to improve the quality of digital impressions. However, information on the accuracy of AI-assisted virtual models is limited. This study aimed to ...

Accuracy of artificial intelligence-based segmentation in maxillofacial structures: a systematic review.

BMC oral health
OBJECTIVE: The aim of this review was to evaluate the accuracy of artificial intelligence (AI) in the segmentation of teeth, jawbone (maxilla, mandible with temporomandibular joint), and mandibular (inferior alveolar) canal in CBCT and CT scans.

Validation of a fully automatic assessment of volume changes in the mandibular condyles following bimaxillary surgery.

International journal of oral and maxillofacial surgery
This study was performed to propose and validate a fully automatic assessment of volume changes in the mandibular condyles following orthognathic surgery. Two sets of cone beam computed tomography scans were included: one with segmentations of comple...

Automatic Segmentation of Bone Graft in Maxillary Sinus via Distance Constrained Network Guided by Prior Anatomical Knowledge.

IEEE journal of biomedical and health informatics
Maxillary Sinus Lifting is a crucial surgical procedure for addressing insufficient alveolar bone mass andsevere resorption in dental implant therapy. To accurately analyze the geometry changesof the bone graft (BG) in the maxillary sinus (MS), it is...