AIMC Topic: Cone-Beam Computed Tomography
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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
Jun 6, 2025
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
Jun 6, 2025
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...
Development and validation of a predictive nomogram for bilateral posterior condylar displacement using cone-beam computed tomography and machine-learning algorithms: a retrospective observational study.
BMC oral health
Jun 5, 2025
BACKGROUND: Temporomandibular disorders (TMDs) are frequently associated with posterior condylar displacement; however, early prediction of this displacement remains a significant challenge. Therefore, in this study, we aimed to develop and evaluate ...
AI-powered segmentation of bifid mandibular canals using CBCT.
BMC oral health
Jun 4, 2025
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...
Quantitative analysis and clinical determinants of orthodontically induced root resorption using automated tooth segmentation from CBCT imaging.
BMC oral health
May 8, 2025
BACKGROUND: Orthodontically induced root resorption (OIRR) is difficult to assess accurately using traditional 2D imaging due to distortion and low sensitivity. While CBCT offers more precise 3D evaluation, manual segmentation remains labor-intensive...
Using deep learning generated CBCT contours for online dose assessment of prostate SABR treatments.
Journal of applied clinical medical physics
Apr 23, 2025
Prostate Stereotactic Ablative Body Radiotherapy (SABR) is an ultra-hypofractionated treatment where small setup errors can lead to higher doses to organs at risk (OARs). Although bowel and bladder preparation protocols reduce inter-fraction variabil...
Towards real-time conformal palliative treatment of spine metastases: A deep learning approach for Hounsfield Unit recovery of cone beam CT images.
Medical physics
Apr 21, 2025
BACKGROUND: The extension of onboard cone-beam CT (CBCT) imaging for real-time treatment planning is constrained by limitations in image quality. Synthetic CT (sCT) generation using deep learning provides a potential solution to these limitations.
Localisation and classification of multi-stage caries on CBCT images with a 3D convolutional neural network.
Clinical oral investigations
Apr 14, 2025
OBJECTIVES: Dental caries remains a significant global health concern. Recognising the diagnostic potential of cone-beam computed tomography (CBCT) in caries assessment, this study aimed to develop an artificial intelligence (AI)-driven tool for accu...
Evaluating the dosimetric and positioning accuracy of a deep learning based synthetic-CT model for liver radiotherapy treatment planning.
Biomedical physics & engineering express
Apr 11, 2025
An MRI-only workflow requires synthetic computed tomography (sCT) images to enable dose calculation. This study evaluated the dosimetric and patient positioning accuracy of deep learning-generated sCT for liver radiotherapy.sCT images were generated ...
Automatic identification of hard and soft tissue landmarks in cone-beam computed tomography via deep learning with diversity datasets: a methodological study.
BMC oral health
Apr 8, 2025
BACKGROUND: Manual landmark detection in cone beam computed tomography (CBCT) for evaluating craniofacial structures relies on medical expertise and is time-consuming. This study aimed to apply a new deep learning method to predict and locate soft an...
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