AIMC Topic: Cone-Beam Computed Tomography
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Context-guided fully convolutional networks for joint craniomaxillofacial bone segmentation and landmark digitization.
Medical image analysis
Nov 23, 2019
Cone-beam computed tomography (CBCT) scans are commonly used in diagnosing and planning surgical or orthodontic treatment to correct craniomaxillofacial (CMF) deformities. Based on CBCT images, it is clinically essential to generate an accurate 3D mo...
Diagnosis of cystic lesions using panoramic and cone beam computed tomographic images based on deep learning neural network.
Oral diseases
Nov 18, 2019
OBJECTIVES: The aim of the current study was to evaluate the detection and diagnosis of three types of odontogenic cystic lesions (OCLs)-odontogenic keratocysts, dentigerous cysts, and periapical cysts-using dental panoramic radiography and cone beam...
Patient-specific reconstruction of volumetric computed tomography images from a single projection view via deep learning.
Nature biomedical engineering
Oct 28, 2019
Tomographic imaging using penetrating waves generates cross-sectional views of the internal anatomy of a living subject. For artefact-free volumetric imaging, projection views from a large number of angular positions are required. Here we show that a...
Segmentation of dental cone-beam CT scans affected by metal artifacts using a mixed-scale dense convolutional neural network.
Medical physics
Sep 13, 2019
PURPOSE: In order to attain anatomical models, surgical guides and implants for computer-assisted surgery, accurate segmentation of bony structures in cone-beam computed tomography (CBCT) scans is required. However, this image segmentation step is of...
3D cone-beam CT of the ankle using a novel twin robotic X-ray system: Assessment of image quality and radiation dose.
European journal of radiology
Sep 7, 2019
PURPOSE: To evaluate image quality (IQ) and radiation dose in cone-beam computed tomography (CBCT) of the ankle using a novel twin robotic X-ray system.
Abdominal artery segmentation method from CT volumes using fully convolutional neural network.
International journal of computer assisted radiology and surgery
Sep 6, 2019
PURPOSE : The purpose of this paper is to present a fully automated abdominal artery segmentation method from a CT volume. Three-dimensional (3D) blood vessel structure information is important for diagnosis and treatment. Information about blood ves...
DeepOrganNet: On-the-Fly Reconstruction and Visualization of 3D / 4D Lung Models from Single-View Projections by Deep Deformation Network.
IEEE transactions on visualization and computer graphics
Aug 22, 2019
This paper introduces a deep neural network based method, i.e., DeepOrganNet, to generate and visualize fully high-fidelity 3D / 4D organ geometric models from single-view medical images with complicated background in real time. Traditional 3D / 4D m...
Machine learning in orthodontics: .
The Angle orthodontist
Aug 12, 2019
OBJECTIVES: To (1) introduce a novel machine learning method and (2) assess maxillary structure variation in unilateral canine impaction for advancing clinically viable information.
Minimally Invasive Approach for Diagnosing TMJ Osteoarthritis.
Journal of dental research
Jul 24, 2019
This study's objectives were to test correlations among groups of biomarkers that are associated with condylar morphology and to apply artificial intelligence to test shape analysis features in a neural network (NN) to stage condylar morphology in te...
A preliminary study of using a deep convolution neural network to generate synthesized CT images based on CBCT for adaptive radiotherapy of nasopharyngeal carcinoma.
Physics in medicine and biology
Jul 16, 2019
This study aims to utilize a deep convolutional neural network (DCNN) for synthesized CT image generation based on cone-beam CT (CBCT) and to apply the images to dose calculations for nasopharyngeal carcinoma (NPC). An encoder-decoder 2D U-Net neural...
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