AIMC Topic: Cone-Beam Computed Tomography
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Weight-bearing CT in foot and ankle pathology.
Orthopaedics & traumatology, surgery & research : OTSR
Dec 13, 2020
Cone-beam scanners (CBCT) enable CT to be performed under weight-bearing - notably for the foot and ankle. The technology is not new: it has been used since 1996 in dental surgery, where it has come to replace panoramic X-ray. What is new is placing ...
Comparison of the suitability of CBCT- and MR-based synthetic CTs for daily adaptive proton therapy in head and neck patients.
Physics in medicine and biology
Dec 5, 2020
Cone-beam computed tomography (CBCT)- and magnetic resonance (MR)-images allow a daily observation of patient anatomy but are not directly suited for accurate proton dose calculations. This can be overcome by creating synthetic CTs (sCT) using deep c...
Automatic Registration Between Dental Cone-Beam CT and Scanned Surface via Deep Pose Regression Neural Networks and Clustered Similarities.
IEEE transactions on medical imaging
Nov 30, 2020
Computerized registration between maxillofacial cone-beam computed tomography (CT) images and a scanned dental model is an essential prerequisite for surgical planning for dental implants or orthognathic surgery. We propose a novel method that perfor...
Predicting spatial esophageal changes in a multimodal longitudinal imaging study via a convolutional recurrent neural network.
Physics in medicine and biology
Nov 27, 2020
Acute esophagitis (AE) occurs among a significant number of patients with locally advanced lung cancer treated with radiotherapy. Early prediction of AE, indicated by esophageal wall expansion, is critical, as it can facilitate the redesign of treatm...
Accuracy of dental implant surgery with robotic position feedback and registration algorithm: An in-vitro study.
Computers in biology and medicine
Nov 26, 2020
BACKGROUND: The purpose of this study was to develop and validate a positioning method with hand-guiding and contact position feedback of robot based on a human-robot collaborative dental implant system (HRCDIS) for robotic guided dental implant surg...
A convolutional neural network-based anthropomorphic model observer for signal-known-statistically and background-known-statistically detection tasks.
Physics in medicine and biology
Nov 24, 2020
The purpose of this study is implementation of an anthropomorphic model observer using a convolutional neural network (CNN) for signal-known-statistically (SKS) and background-known-statistically (BKS) detection tasks. We conduct SKS/BKS detection ta...
Age estimation based on 3D pulp chamber segmentation of first molars from cone-beam-computed tomography by integrated deep learning and level set.
International journal of legal medicine
Nov 13, 2020
OBJECTIVES: To develop an automatic segmentation method to segment the pulp chamber of first molars from 3D cone-beam-computed tomography (CBCT) images, and to estimate ages by calculated pulp volumes.
Differentiated Backprojection Domain Deep Learning for Conebeam Artifact Removal.
IEEE transactions on medical imaging
Oct 28, 2020
Conebeam CT using a circular trajectory is quite often used for various applications due to its relative simple geometry. For conebeam geometry, Feldkamp, Davis and Kress algorithm is regarded as the standard reconstruction method, but this algorithm...
Self-contained deep learning-based boosting of 4D cone-beam CT reconstruction.
Medical physics
Oct 15, 2020
PURPOSE: Four-dimensional cone-beam computed tomography (4D CBCT) imaging has been suggested as a solution to account for interfraction motion variability of moving targets like lung and liver during radiotherapy (RT) of moving targets. However, due ...
4D-AirNet: a temporally-resolved CBCT slice reconstruction method synergizing analytical and iterative method with deep learning.
Physics in medicine and biology
Sep 11, 2020
Four-dimensional (4D) cone-beam CT (CBCT) reconstructs temporally-resolved phases of 3D volumes often with the same amount of projection data that are meant for reconstructing a single 3D volume. 4D CBCT is a sparse-data problem that is very challeng...
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