AIMC Topic: Four-Dimensional Computed Tomography

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Development of realistic multi-contrast textured XCAT (MT-XCAT) phantoms using a dual-discriminator conditional-generative adversarial network (D-CGAN).

Physics in medicine and biology Mar 19, 2020
Develop a machine learning-based method to generate multi-contrast anatomical textures in the 4D extended cardiac-torso (XCAT) phantom for more realistic imaging simulations. As a pilot study, we synthesize CT and CBCT textures in the chest region. F...
Humans Contrast Media Phantoms, Imaging Four-Dimensional Computed Tomography Machine Learning Pilot Projects
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Real-time markerless tumour tracking with patient-specific deep learning using a personalised data generation strategy: proof of concept by phantom study.

The British journal of radiology Feb 28, 2020
OBJECTIVE: For real-time markerless tumour tracking in stereotactic lung radiotherapy, we propose a different approach which uses patient-specific deep learning (DL) using a personalised data generation strategy, avoiding the need for collection of a...
Humans Deep Learning Phantoms, Imaging Movement Four-Dimensional Computed Tomography Fluoroscopy Feasibility Studies Image Processing, Computer-Assisted Lung Neoplasms
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LungRegNet: An unsupervised deformable image registration method for 4D-CT lung.

Medical physics Feb 26, 2020
PURPOSE: To develop an accurate and fast deformable image registration (DIR) method for four-dimensional computed tomography (4D-CT) lung images. Deep learning-based methods have the potential to quickly predict the deformation vector field (DVF) in ...
Four-Dimensional Computed Tomography Image Processing, Computer-Assisted Unsupervised Machine Learning Humans Lung
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A deep learning method for producing ventilation images from 4DCT: First comparison with technegas SPECT ventilation.

Medical physics Jan 28, 2020
PURPOSE: The purpose of this study is to develop a deep learning (DL) method for producing four-dimensional computed tomography (4DCT) ventilation imaging and to evaluate the accuracy of the DL-based ventilation imaging against single-photon emission...
Tomography, Emission-Computed, Single-Photon Four-Dimensional Computed Tomography Humans Deep Learning Image Processing, Computer-Assisted Pulmonary Ventilation
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A multi-scale framework with unsupervised joint training of convolutional neural networks for pulmonary deformable image registration.

Physics in medicine and biology Jan 13, 2020
To achieve accurate and fast deformable image registration (DIR) for pulmonary CT, we proposed a Multi-scale DIR framework with unsupervised Joint training of Convolutional Neural Network (MJ-CNN). MJ-CNN contains three models at multi-scale levels f...
Humans Neural Networks, Computer Four-Dimensional Computed Tomography Image Processing, Computer-Assisted Lung Neoplasms
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A fast and scalable method for quality assurance of deformable image registration on lung CT scans using convolutional neural networks.

Medical physics Nov 19, 2019
PURPOSE: To develop and evaluate a method to automatically identify and quantify deformable image registration (DIR) errors between lung computed tomography (CT) scans for quality assurance (QA) purposes.
Quality Control Four-Dimensional Computed Tomography Time Factors Image Processing, Computer-Assisted Neural Networks, Computer Humans Lung
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Stacked Bidirectional Convolutional LSTMs for Deriving 3D Non-Contrast CT From Spatiotemporal 4D CT.

IEEE transactions on medical imaging Sep 2, 2019
The imaging workup in acute stroke can be simplified by deriving non-contrast CT (NCCT) from CT perfusion (CTP) images. This results in reduced workup time and radiation dose. To achieve this, we present a stacked bidirectional convolutional LSTM (C-...
Humans Female Aged Brain Perfusion Imaging Deep Learning Male Four-Dimensional Computed Tomography Stroke Middle Aged
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Using a deep neural network for four-dimensional CT artifact reduction in image-guided radiotherapy.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) Aug 17, 2019
INTRODUCTION: Breathing artifact may affect the quality of four-dimensional computed tomography (4DCT) images. We developed a deep neural network (DNN)-based artifact reduction method.
Four-Dimensional Computed Tomography Humans Artifacts Neoplasms Image Processing, Computer-Assisted Radiotherapy, Image-Guided Deep Learning Quality Control
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Technical Note: Deriving ventilation imaging from 4DCT by deep convolutional neural network.

Medical physics Mar 12, 2019
PURPOSE: Ventilation images can be derived from four-dimensional computed tomography (4DCT) by analyzing the change in HU values and deformable vector fields between different respiration phases of computed tomography (CT). As deformable image regist...
Deep Learning Image Processing, Computer-Assisted Pulmonary Ventilation Humans Four-Dimensional Computed Tomography
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Real-time tumor tracking using fluoroscopic imaging with deep neural network analysis.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) Feb 25, 2019
PURPOSE: To improve respiratory gating accuracy and treatment throughput, we developed a fluoroscopic markerless tumor tracking algorithm based on a deep neural network (DNN).
Four-Dimensional Computed Tomography Liver Neoplasms Lung Neoplasms Humans Retrospective Studies Fluoroscopy Image Processing, Computer-Assisted Time Factors Neural Networks, Computer
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