AIMC Topic: Mandible

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Panoramic radiographic features for machine learning based detection of mandibular third molar root and inferior alveolar canal contact.

Scientific reports
This study uses machine learning (ML) to elucidate the contact relationship between the mandibular third molar (M3M) and the inferior alveolar canal (IAC), leading to three major contributions; (1) The first publicly accessible PR image dataset with ...

Assessment of hard tissue changes after horizontal guided bone regeneration with the aid of deep learning CBCT segmentation.

Clinical oral investigations
OBJECTIVES: To investigate the performance of a deep learning (DL) model for segmenting cone-beam computed tomography (CBCT) scans taken before and after mandibular horizontal guided bone regeneration (GBR) to evaluate hard tissue changes.

Feasibility of occlusal plane in predicting the changes in anteroposterior mandibular position: a comprehensive analysis using deep learning-based three-dimensional models.

BMC oral health
BACKGROUND: A comprehensive analysis of the occlusal plane (OP) inclination in predicting anteroposterior mandibular position (APMP) changes is still lacking. This study aimed to analyse the relationships between inclinations of different OPs and APM...

Segmentation of the iliac crest from CT-data for virtual surgical planning of facial reconstruction surgery using deep learning.

Scientific reports
BACKGROUND AND OBJECTIVES: For the planning of surgical procedures involving the bony reconstruction of the mandible, the autologous iliac crest graft, along with the fibula graft, has become established as a preferred donor region. While computer-as...

The use of artificial intelligence in predicting maximal intercuspal position: A feasibility study.

Journal of prosthodontic research
PURPOSE: Artificial intelligence (AI) may be used to learn and predict the maxillomandibular relationship, particularly when the number of occluding teeth pairs is insufficient. This study aimed to investigate the feasibility of training a new two-st...

Efficacy of a deep learning system for automatic analysis of the comprehensive spatial relationship between the mandibular third molar and inferior alveolar canal on panoramic radiographs.

Oral surgery, oral medicine, oral pathology and oral radiology
OBJECTIVE: To develop and evaluate a deep learning (DL) system for predicting the contact and relative position relationships between the mandibular third molar (M3) and inferior alveolar canal (IAC) using panoramic radiographs (PRs) for preoperative...

Limitations of panoramic radiographs in predicting mandibular wisdom tooth extraction and the potential of deep learning models to overcome them.

Scientific reports
Surgeons routinely interpret preoperative radiographic images for estimating the shape and position of the tooth prior to performing tooth extraction. In this study, we aimed to predict the difficulty of lower wisdom tooth extraction using only panor...

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
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...

Enhancing artificial intelligence-driven sleep apnea diagnosis: The critical importance of input signal proficiency with a focus on mandibular jaw movements.

Journal of prosthodontics : official journal of the American College of Prosthodontists
PURPOSE: This review aims to highlight the pivotal role of the mandibular jaw movement (MJM) signal in advancing artificial intelligence (AI)-powered technologies for diagnosing obstructive sleep apnea (OSA).