AIMC Topic: Cone-Beam Computed Tomography
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Enhancing synthetic pelvic CT generation from CBCT using vision transformer with adaptive fourier neural operators.
Biomedical physics & engineering express
Aug 11, 2025
This study introduces a novel approach to improve Cone Beam CT (CBCT) image quality by developing a synthetic CT (sCT) generation method using CycleGAN with a Vision Transformer (ViT) and an Adaptive Fourier Neural Operator (AFNO).A dataset of 20 pro...
Deep learning-based real-time detection of head and neck tumors during radiation therapy.
Physics in medicine and biology
Jul 31, 2025
Clinical drivers for real-time head and neck (H&N) tumor tracking during radiation therapy (RT) are accounting for motion caused by changes to the immobilization mask fit, and to reduce mask-related patient distress by replacing the masks with patien...
Multimodal deep learning for cephalometric landmark detection and treatment prediction.
Scientific reports
Jul 12, 2025
In orthodontics and maxillofacial surgery, accurate cephalometric analysis and treatment outcome prediction are critical for clinical decision-making. Traditional approaches rely on manual landmark identification, which is time-consuming and subject ...
MMDental - A multimodal dataset of tooth CBCT images with expert medical records.
Scientific data
Jul 9, 2025
In the rapidly evolving field of dental intelligent healthcare, where Artificial Intelligence (AI) plays a pivotal role, the demand for multimodal datasets is critical. Existing public datasets are primarily composed of single-modal data, predominant...
Comparison of 2D, 2.5D, and 3D segmentation networks for mandibular canals in CBCT images: a study on public and external datasets.
BMC oral health
Jul 8, 2025
The purpose of this study was to compare the performances of 2D, 2.5D, and 3D CNN-based segmentation networks, along with a 3D vision transformer-based segmentation network, for segmenting mandibular canals (MCs) on the public and external CBCT datas...
Performance of two different artificial intelligence models in dental implant planning among four different implant planning software: a comparative study.
BMC oral health
Jul 2, 2025
BACKGROUND: The integration of artificial intelligence (AI) in dental implant planning has emerged as a transformative approach to enhance diagnostic accuracy and efficiency. This study aimed to evaluate the performance of two object detection models...
Automatic detection of orthodontically induced external root resorption based on deep convolutional neural networks using CBCT images.
Scientific reports
Jul 2, 2025
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
Jul 1, 2025
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.
Quantitative and automatic plan-of-the-day assessment to facilitate adaptive radiotherapy in cervical cancer.
Physics in medicine and biology
Jun 23, 2025
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
Jun 14, 2025
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...
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