AIMC Topic: Magnetic Resonance Imaging

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Data-driven self-calibration and reconstruction for non-cartesian wave-encoded single-shot fast spin echo using deep learning.

Journal of magnetic resonance imaging : JMRI Jul 19, 2019
BACKGROUND: Current self-calibration and reconstruction methods for wave-encoded single-shot fast spin echo imaging (SSFSE) requires long computational time, especially when high accuracy is needed.
Artifacts Calibration Female Aged Young Adult Adult Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Male Middle Aged Humans Prospective Studies
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Automatic spondylolisthesis grading from MRIs across modalities using faster adversarial recognition network.

Medical image analysis Jul 19, 2019
Grading spondylolisthesis into several stages from MRI images is challenging because detecting critical vertebrae and locating landmarks in images of different characteristics is difficult. We propose Faster Adversarial Recognition (FAR) network to a...
Anatomic Landmarks Image Interpretation, Computer-Assisted Pattern Recognition, Automated Humans Spondylolisthesis Neural Networks, Computer Severity of Illness Index Magnetic Resonance Imaging
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Fast and accurate reconstruction of human lung gas MRI with deep learning.

Magnetic resonance in medicine Jul 19, 2019
PURPOSE: To fast and accurately reconstruct human lung gas MRI from highly undersampled k-space using deep learning.
Magnetic Resonance Imaging Solitary Pulmonary Nodule Tuberculosis, Pulmonary Healthy Volunteers Deep Learning Imaging, Three-Dimensional Image Processing, Computer-Assisted Inflammation Fourier Analysis Protons Xenon Isotopes Smoking Respiration Signal-To-Noise Ratio Bronchiectasis Aged Young Adult Adult Pulmonary Disease, Chronic Obstructive Asthma Male Middle Aged Lung Prospective Studies Retrospective Studies Female Reproducibility of Results Humans Algorithms
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Machine Learning Approaches for Automated Lesion Detection in Microwave Breast Imaging Clinical Data.

Scientific reports Jul 19, 2019
Breast lesion detection employing state of the art microwave systems provide a safe, non-ionizing technique that can differentiate healthy and non-healthy tissues by exploiting their dielectric properties. In this paper, a microwave apparatus for bre...
Scattering, Radiation Microwave Imaging Female Breast Humans Breast Neoplasms Clinical Trials as Topic Magnetic Resonance Imaging Neural Networks, Computer ROC Curve Statistics, Nonparametric Algorithms Mammography Dielectric Spectroscopy Support Vector Machine Equipment Design Ultrasonography, Mammary
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Disentangled representation learning in cardiac image analysis.

Medical image analysis Jul 18, 2019
Typically, a medical image offers spatial information on the anatomy (and pathology) modulated by imaging specific characteristics. Many imaging modalities including Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) can be interpreted in ...
Humans Supervised Machine Learning Tomography, X-Ray Computed Image Interpretation, Computer-Assisted Cardiovascular Diseases Datasets as Topic Magnetic Resonance Imaging
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k-Space deep learning for reference-free EPI ghost correction.

Magnetic resonance in medicine Jul 18, 2019
PURPOSE: Nyquist ghost artifacts in echo planar imaging (EPI) are originated from phase mismatch between the even and odd echoes. However, conventional correction methods using reference scans often produce erroneous results especially in high-field ...
Humans Deep Learning Artifacts Neural Networks, Computer Image Processing, Computer-Assisted Image Enhancement Algorithms Models, Theoretical Signal-To-Noise Ratio Brain Phantoms, Imaging Magnetic Resonance Imaging Radionuclide Imaging Reproducibility of Results Echo-Planar Imaging
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Fully Automated Postlumpectomy Breast Margin Assessment Utilizing Convolutional Neural Network Based Optical Coherence Tomography Image Classification Method.

Academic radiology Jul 17, 2019
BACKGROUND: The purpose of this study was to develop a deep learning classification approach to distinguish cancerous from noncancerous regions within optical coherence tomography (OCT) images of breast tissue for potential use in an intraoperative s...
Humans Neural Networks, Computer Algorithms Female Breast Neoplasms Image Processing, Computer-Assisted Margins of Excision Magnetic Resonance Imaging Mastectomy, Segmental Tomography, Optical Coherence Breast Postoperative Period
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Deep Learning of Static and Dynamic Brain Functional Networks for Early MCI Detection.

IEEE transactions on medical imaging Jul 17, 2019
While convolutional neural network (CNN) has been demonstrating powerful ability to learn hierarchical spatial features from medical images, it is still difficult to apply it directly to resting-state functional MRI (rs-fMRI) and the derived brain fu...
Deep Learning Cognitive Dysfunction Magnetic Resonance Imaging Alzheimer Disease Brain Humans Image Interpretation, Computer-Assisted Aged Aged, 80 and over Middle Aged
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Utility of deep learning super-resolution in the context of osteoarthritis MRI biomarkers.

Journal of magnetic resonance imaging : JMRI Jul 16, 2019
BACKGROUND: Super-resolution is an emerging method for enhancing MRI resolution; however, its impact on image quality is still unknown.
Osteoarthritis Humans Retrospective Studies Biomarkers Reproducibility of Results Deep Learning Magnetic Resonance Imaging
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MRI-based treatment planning for proton radiotherapy: dosimetric validation of a deep learning-based liver synthetic CT generation method.

Physics in medicine and biology Jul 16, 2019
Magnetic resonance imaging (MRI) has been widely used in combination with computed tomography (CT) radiation therapy because MRI improves the accuracy and reliability of target delineation due to its superior soft tissue contrast over CT. The MRI-onl...
Humans Retrospective Studies Tomography, X-Ray Computed Reproducibility of Results Image Processing, Computer-Assisted Radiotherapy Planning, Computer-Assisted Deep Learning Magnetic Resonance Imaging Radiotherapy Dosage Liver Neoplasms Radiography, Abdominal Carcinoma, Hepatocellular
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