AIMC Topic: Phantoms, Imaging

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Noise Adaptation Generative Adversarial Network for Medical Image Analysis.

IEEE transactions on medical imaging Sep 30, 2019
Machine learning has been widely used in medical image analysis under an assumption that the training and test data are under the same feature distributions. However, medical images from difference devices or the same device with different parameter ...
Bone and Bones Phantoms, Imaging Humans Image Processing, Computer-Assisted Muscle, Skeletal Tomography, Optical Coherence Machine Learning Deep Learning Ultrasonography
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Memory-efficient 2.5D convolutional transformer networks for multi-modal deformable registration with weak label supervision applied to whole-heart CT and MRI scans.

International journal of computer assisted radiology and surgery Sep 19, 2019
PURPOSE : Despite its potential for improvements through supervision, deep learning-based registration approaches are difficult to train for large deformations in 3D scans due to excessive memory requirements. METHODS : We propose a new 2.5D convolut...
Tomography, X-Ray Computed Deep Learning Magnetic Resonance Imaging Phantoms, Imaging Equipment Design Heart Humans Neural Networks, Computer
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Combined tract segmentation and orientation mapping for bundle-specific tractography.

Medical image analysis Sep 12, 2019
While the major white matter tracts are of great interest to numerous studies in neuroscience and medicine, their manual dissection in larger cohorts from diffusion MRI tractograms is time-consuming, requires expert knowledge and is hard to reproduce...
Humans Brain Mapping Datasets as Topic Machine Learning Image Processing, Computer-Assisted Diffusion Tensor Imaging White Matter Neural Pathways Phantoms, Imaging
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CIGuide: in situ augmented reality laser guidance.

International journal of computer assisted radiology and surgery Sep 11, 2019
PURPOSE : A robotic intraoperative laser guidance system with hybrid optic-magnetic tracking for skull base surgery is presented. It provides in situ augmented reality guidance for microscopic interventions at the lateral skull base with minimal ment...
Surgery, Computer-Assisted Cadaver Needles Equipment Design Neurosurgical Procedures Augmented Reality Phantoms, Imaging Skull Base Humans Robotics
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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.
Signal-To-Noise Ratio Ankle Joint Phantoms, Imaging X-Rays Tomography Scanners, X-Ray Computed Cadaver Artifacts Radiation Dosage Cone-Beam Computed Tomography Robotics Humans Equipment Design
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Deep Learning Based Noise Reduction for Brain MR Imaging: Tests on Phantoms and Healthy Volunteers.

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine Sep 4, 2019
PURPOSE: To test whether our proposed denoising approach with deep learning-based reconstruction (dDLR) can effectively denoise brain MR images.
Brain Deep Learning Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Humans Signal-To-Noise Ratio Phantoms, Imaging
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A deep learning method for image-based subject-specific local SAR assessment.

Magnetic resonance in medicine Sep 4, 2019
PURPOSE: Local specific absorption rate (SAR) cannot be measured and is usually evaluated by offline numerical simulations using generic body models that of course will differ from the patient's anatomy. An additional safety margin is needed to inclu...
Signal-To-Noise Ratio Phantoms, Imaging Prostatic Neoplasms Prostate Healthy Volunteers Computer Simulation Reproducibility of Results Male Magnetic Resonance Imaging Models, Statistical Neural Networks, Computer Deep Learning Humans Algorithms Image Processing, Computer-Assisted Databases, Factual
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Range and dose verification in proton therapy using proton-induced positron emitters and recurrent neural networks (RNNs).

Physics in medicine and biology Sep 4, 2019
Online proton range/dose verification based on measurements of proton-induced positron emitters is a promising strategy for quality assurance in proton therapy. Because of the nonlinear correlation between the dose distribution and the activity distr...
Humans Neural Networks, Computer Tomography, X-Ray Computed Positron-Emission Tomography Feasibility Studies Phantoms, Imaging Proton Therapy Electrons Uncertainty
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PET image denoising using unsupervised deep learning.

European journal of nuclear medicine and molecular imaging Aug 29, 2019
PURPOSE: Image quality of positron emission tomography (PET) is limited by various physical degradation factors. Our study aims to perform PET image denoising by utilizing prior information from the same patient. The proposed method is based on unsup...
Middle Aged Aged, 80 and over Image Enhancement Positron-Emission Tomography Adult Signal-To-Noise Ratio Deep Learning Lung Neoplasms Humans Male Phantoms, Imaging Unsupervised Machine Learning Image Processing, Computer-Assisted Quality Control Female Aged
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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...
Humans Neural Networks, Computer Algorithms Imaging, Three-Dimensional Lung Phantoms, Imaging Lung Neoplasms Deep Learning Cone-Beam Computed Tomography
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