AIMC Topic: Cone-Beam Computed Tomography

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Artificial Intelligence for the Computer-aided Detection of Periapical Lesions in Cone-beam Computed Tomographic Images.

Journal of endodontics May 8, 2020
INTRODUCTION: The aim of this study was to use a Deep Learning (DL) algorithm for the automated segmentation of cone-beam computed tomographic (CBCT) images and the detection of periapical lesions.
Computers Sensitivity and Specificity Cone-Beam Computed Tomography Artificial Intelligence
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Comparison of CBCT based synthetic CT methods suitable for proton dose calculations in adaptive proton therapy.

Physics in medicine and biology Apr 28, 2020
In-room imaging is a prerequisite for adaptive proton therapy. The use of onboard cone-beam computed tomography (CBCT) imaging, which is routinely acquired for patient position verification, can enable daily dose reconstructions and plan adaptation d...
Cone-Beam Computed Tomography Image Processing, Computer-Assisted Head and Neck Neoplasms Male Middle Aged Proton Therapy Radiometry Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Neural Networks, Computer Female Aged, 80 and over Adult Aged Humans
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Deep Learning Method for Mandibular Canal Segmentation in Dental Cone Beam Computed Tomography Volumes.

Scientific reports Apr 3, 2020
Accurate localisation of mandibular canals in lower jaws is important in dental implantology, in which the implant position and dimensions are currently determined manually from 3D CT images by medical experts to avoid damaging the mandibular nerve i...
Imaging, Three-Dimensional Mandible Deep Learning Cone-Beam Computed Tomography Humans
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Automatic mandibular canal detection using a deep convolutional neural network.

Scientific reports Mar 31, 2020
The practicability of deep learning techniques has been demonstrated by their successful implementation in varied fields, including diagnostic imaging for clinicians. In accordance with the increasing demands in the healthcare industry, techniques fo...
Humans Mandible Temporomandibular Joint Disorders Mandibular Nerve Cone-Beam Computed Tomography Imaging, Three-Dimensional Patient Care Planning Adult Male Deep Learning Adolescent Aged Aged, 80 and over Middle Aged Neural Networks, Computer Young Adult Female
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Technical Note: 3D localization of lung tumors on cone beam CT projections via a convolutional recurrent neural network.

Medical physics Jan 28, 2020
PURPOSE: To design a convolutional recurrent neural network (CRNN) that calculates three-dimensional (3D) positions of lung tumors from continuously acquired cone beam computed tomography (CBCT) projections, and facilitates the sorting and reconstruc...
Imaging, Three-Dimensional Lung Neoplasms Humans Neural Networks, Computer Cone-Beam Computed Tomography
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Convolutional neural network enhancement of fast-scan low-dose cone-beam CT images for head and neck radiotherapy.

Physics in medicine and biology Jan 27, 2020
To improve image quality and CT number accuracy of fast-scan low-dose cone-beam computed tomography (CBCT) through a deep-learning convolutional neural network (CNN) methodology for head-and-neck (HN) radiotherapy. Fifty-five paired CBCT and CT image...
Humans Retrospective Studies Cone-Beam Computed Tomography Neural Networks, Computer Radiotherapy Planning, Computer-Assisted Image Processing, Computer-Assisted Image Enhancement Head and Neck Neoplasms Signal-To-Noise Ratio
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Synthetic CT generation from CBCT images via deep learning.

Medical physics Jan 13, 2020
PURPOSE: Cone-beam computed tomography (CBCT) scanning is used daily or weekly (i.e., on-treatment CBCT) for accurate patient setup in image-guided radiotherapy. However, inaccuracy of CT numbers prevents CBCT from performing advanced tasks such as d...
Image Processing, Computer-Assisted Humans Deep Learning Cone-Beam Computed Tomography
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Visual enhancement of Cone-beam CT by use of CycleGAN.

Medical physics Jan 3, 2020
PURPOSE: Cone-beam computed tomography (CBCT) offers advantages over conventional fan-beam CT in that it requires a shorter time and less exposure to obtain images. However, CBCT images suffer from low soft-tissue contrast, noise, and artifacts compa...
Humans Image Processing, Computer-Assisted Cone-Beam Computed Tomography Deep Learning
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Twin Robotic X-Ray System for 3D Cone-Beam CT of the Wrist: An Evaluation of Image Quality and Radiation Dose.

AJR. American journal of roentgenology Dec 4, 2019
The purpose of this study was to assess image quality and radiation dose of a novel twin robotic x-ray system's 3D cone-beam CT (CBCT) function for the depiction of cadaveric wrists. Sixteen cadaveric wrists were scanned using dedicated low-dose an...
Cadaver Artifacts Patient Positioning Wrist Joint Humans Imaging, Three-Dimensional Radiation Dosage Cone-Beam Computed Tomography Robotics
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Liver tumor segmentation in CT volumes using an adversarial densely connected network.

BMC bioinformatics Dec 2, 2019
BACKGROUND: Malignant liver tumor is one of the main causes of human death. In order to help physician better diagnose and make personalized treatment schemes, in clinical practice, it is often necessary to segment and visualize the liver tumor from ...
Algorithms Tomography, X-Ray Computed Cone-Beam Computed Tomography Humans Liver Neoplasms Neural Networks, Computer Image Processing, Computer-Assisted
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