AIMC Topic: Cone-Beam Computed Tomography

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Automatic detection of orthodontically induced external root resorption based on deep convolutional neural networks using CBCT images.

Scientific reports
Orthodontically-induced external root resorption (OIERR) is among the most common risks in orthodontic treatment. Traditional OIERR diagnosis is limited by subjective judgement as well as cumbersome manual measurement. The research aims to develop an...

Automated 3D segmentation of the hyoid bone in CBCT using nnU-Net v2: a retrospective study on model performance and potential clinical utility.

BMC medical imaging
OBJECTIVE: This study aimed to identify the hyoid bone (HB) using the nnU-Net based artificial intelligence (AI) model in cone beam computed tomography (CBCT) images and assess the model's success in automatic segmentation.

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...

Quantitative and automatic plan-of-the-day assessment to facilitate adaptive radiotherapy in cervical cancer.

Physics in medicine and biology
To facilitate implementation of plan-of-the-day (POTD) selection for treating locally advanced cervical cancer (LACC), we developed a POTD assessment tool for CBCT-guided radiotherapy (RT). A female pelvis segmentation model (U-Seg3) is combined with...

FDTooth: Intraoral Photographs and CBCT Images for Fenestration and Dehiscence Detection.

Scientific data
Fenestration and dehiscence (FD) pose significant challenges in dental treatments as they adversely affect oral health. Although cone-beam computed tomography (CBCT) provides precise diagnostics, its extensive time requirements and radiation exposure...

Cone-beam computed tomography-based online adaptive radiotherapy of esophageal cancer in the neoadjuvant setting: Dosimetric analysis, toxicity and treatment response.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: Chemoradiotherapy (CRT) followed by surgery is a treatment option for esophageal cancer (EC). However, concerns persist regarding cardiopulmonary toxicity and inconsistent daily target coverage due to anatomical changes. To ad...

Application of Mask R-CNN for automatic recognition of teeth and caries in cone-beam computerized tomography.

BMC oral health
OBJECTIVES: Deep convolutional neural networks (CNNs) are advancing rapidly in medical research, demonstrating promising results in diagnosis and prediction within radiology and pathology. This study evaluates the efficacy of deep learning algorithms...

AI-powered segmentation of bifid mandibular canals using CBCT.

BMC oral health
OBJECTIVE: Accurate segmentation of the mandibular and bifid canals is crucial in dental implant planning to ensure safe implant placement, third molar extractions and other surgical interventions. The objective of this study is to develop and valida...

Impact of artificial intelligence assistance on diagnosing periapical radiolucencies: A randomized controlled trial.

Journal of dentistry
OBJECTIVES: This randomized controlled trial aimed to evaluate the impact of artificial intelligence (AI) assistance on dentists' diagnostic accuracy, confidence, and treatment decisions when detecting periapical radiolucencies (PRs) on panoramic rad...