AIMC Topic: Phantoms, Imaging

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Deep residual network for off-resonance artifact correction with application to pediatric body MRA with 3D cones.

Magnetic resonance in medicine May 22, 2019
PURPOSE: To enable rapid imaging with a scan time-efficient 3D cones trajectory with a deep-learning off-resonance artifact correction technique.
Magnetic Resonance Angiography Phantoms, Imaging Pulmonary Veins Male Deep Learning Child, Preschool Child Imaging, Three-Dimensional Humans Artifacts Female
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Domain Progressive 3D Residual Convolution Network to Improve Low-Dose CT Imaging.

IEEE transactions on medical imaging May 17, 2019
The wide applications of X-ray computed tomography (CT) bring low-dose CT (LDCT) into a clinical prerequisite, but reducing the radiation exposure in CT often leads to significantly increased noise and artifacts, which might lower the judgment accura...
Humans Algorithms Tomography, X-Ray Computed Artifacts Thorax Phantoms, Imaging Deep Learning Imaging, Three-Dimensional Abdomen
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Image Quality Improvement of Hand-Held Ultrasound Devices With a Two-Stage Generative Adversarial Network.

IEEE transactions on bio-medical engineering Apr 24, 2019
As a widely used imaging modality in the medical field, ultrasound has been applied in community medicine, rural medicine, and even telemedicine in recent years. Therefore, the development of portable ultrasound devices has become a popular research ...
Phantoms, Imaging Machine Learning Algorithms Humans Ultrasonography Image Processing, Computer-Assisted Equipment Design Carotid Arteries
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Augmentation of CBCT Reconstructed From Under-Sampled Projections Using Deep Learning.

IEEE transactions on medical imaging Apr 23, 2019
Edges tend to be over-smoothed in total variation (TV) regularized under-sampled images. In this paper, symmetric residual convolutional neural network (SR-CNN), a deep learning based model, was proposed to enhance the sharpness of edges and detailed...
Humans Algorithms Lung Deep Learning Lung Neoplasms Cone-Beam Computed Tomography Phantoms, Imaging Image Processing, Computer-Assisted
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Learning soft tissue behavior of organs for surgical navigation with convolutional neural networks.

International journal of computer assisted radiology and surgery Apr 16, 2019
PURPOSE: In surgical navigation, pre-operative organ models are presented to surgeons during the intervention to help them in efficiently finding their target. In the case of soft tissue, these models need to be deformed and adapted to the current si...
Liver Phantoms, Imaging Organ Motion Neural Networks, Computer Computer Simulation Computer Systems Humans
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Learning to Reconstruct Computed Tomography Images Directly From Sinogram Data Under A Variety of Data Acquisition Conditions.

IEEE transactions on medical imaging Apr 11, 2019
Computed tomography (CT) is widely used in medical diagnosis and non-destructive detection. Image reconstruction in CT aims to accurately recover pixel values from measured line integrals, i.e., the summed pixel values along straight lines. Provided ...
Head Radiography, Thoracic Phantoms, Imaging Image Processing, Computer-Assisted Abdomen Coronary Vessels Humans Tomography, X-Ray Computed Deep Learning
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Image domain dual material decomposition for dual-energy CT using butterfly network.

Medical physics Apr 1, 2019
PURPOSE: Dual-energy CT (DECT) has been increasingly used in imaging applications because of its capability for material differentiation. However, material decomposition suffers from magnified noise from two CT images of independent scans, leading to...
Tomography, X-Ray Computed Image Processing, Computer-Assisted Abdomen Humans Neural Networks, Computer Algorithms Phantoms, Imaging Head Bone and Bones
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Ultrafast (milliseconds), multidimensional RF pulse design with deep learning.

Magnetic resonance in medicine Mar 30, 2019
PURPOSE: Some advanced RF pulses, like multidimensional RF pulses, are often long and require substantial computation time because of a number of constraints and requirements, sometimes hampering clinical use. However, the pulses offer opportunities ...
Time Factors Radio Waves Magnetic Resonance Imaging Humans Databases, Factual Phantoms, Imaging Male Deep Learning
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Analysis of a CT patient dose database with an unsupervised clustering approach.

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) Mar 29, 2019
PURPOSE: This study investigated the benefits of implementing a cluster analysis technique to extract relevant information from a computed tomography (CT) dose registry archive.
Unsupervised Machine Learning Databases, Factual Radiation Dosage Registries Tomography, X-Ray Computed Phantoms, Imaging Data Mining Cluster Analysis Humans Software
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Intact metabolite spectrum mining by deep learning in proton magnetic resonance spectroscopy of the brain.

Magnetic resonance in medicine Mar 12, 2019
PURPOSE: To develop a robust method for brain metabolite quantification in proton magnetic resonance spectroscopy ( H-MRS) using a convolutional neural network (CNN) that maps in vivo brain spectra that are typically degraded by low SNR, line broaden...
Phantoms, Imaging Proton Magnetic Resonance Spectroscopy Protons Amino Acids Young Adult gamma-Aminobutyric Acid Male Brain Chemistry Deep Learning Image Processing, Computer-Assisted Humans Magnetic Resonance Imaging Brain
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