AIMC Topic: Echo-Planar Imaging

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Streamlined magnetic resonance fingerprinting: Fast whole-brain coverage with deep-learning based parameter estimation.

NeuroImage Jun 5, 2021
Magnetic resonance fingerprinting (MRF) is a quantitative MRI (qMRI) framework that provides simultaneous estimates of multiple relaxation parameters as well as metrics of field inhomogeneity in a single acquisition. However, current challenges exist...
Humans Neuroimaging Phantoms, Imaging Neural Networks, Computer Monte Carlo Method Deep Learning Echo-Planar Imaging Image Processing, Computer-Assisted
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Distortion correction of single-shot EPI enabled by deep-learning.

NeuroImage Jul 16, 2020
PURPOSE: A distortion correction method for single-shot EPI was proposed. Point-spread-function encoded EPI (PSF-EPI) images were used as the references to correct traditional EPI images based on deep neural network.
Neuroimaging Diffusion Magnetic Resonance Imaging Echo-Planar Imaging Adult Deep Learning Models, Theoretical Humans Brain
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An unsupervised deep learning technique for susceptibility artifact correction in reversed phase-encoding EPI images.

Magnetic resonance imaging May 12, 2020
Echo planar imaging (EPI) is a fast and non-invasive magnetic resonance imaging technique that supports data acquisition at high spatial and temporal resolutions. However, susceptibility artifacts, which cause the misalignment to the underlying struc...
Image Processing, Computer-Assisted Magnetic Resonance Imaging Unsupervised Machine Learning Humans Artifacts Brain Echo-Planar Imaging Deep Learning
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Test-retest reliability of spatial patterns from resting-state functional MRI using the restricted Boltzmann machine and hierarchically organized spatial patterns from the deep belief network.

Journal of neuroscience methods Oct 15, 2019
BACKGROUND: Restricted Boltzmann machines (RBMs), including greedy layer-wise trained RBMs as part of a deep belief network (DBN), have the ability to identify spatial patterns (SPs; functional networks) in resting-state fMRI (rfMRI) data. However, t...
Brain Reproducibility of Results Adult Pattern Recognition, Automated Humans Neural Networks, Computer Default Mode Network Connectome Nerve Net Echo-Planar 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 ...
Image Enhancement Signal-To-Noise Ratio Radionuclide Imaging Phantoms, Imaging Models, Theoretical Magnetic Resonance Imaging Artifacts Echo-Planar Imaging Humans Neural Networks, Computer Algorithms Deep Learning Image Processing, Computer-Assisted Brain Reproducibility of Results
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Highly accelerated multishot echo planar imaging through synergistic machine learning and joint reconstruction.

Magnetic resonance in medicine May 20, 2019
PURPOSE: To introduce a combined machine learning (ML)- and physics-based image reconstruction framework that enables navigator-free, highly accelerated multishot echo planar imaging (msEPI) and demonstrate its application in high-resolution structur...
Algorithms Brain Humans Image Processing, Computer-Assisted Echo-Planar Imaging Machine Learning
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Incorporation of a spectral model in a convolutional neural network for accelerated spectral fitting.

Magnetic resonance in medicine Jan 21, 2019
PURPOSE: MRSI has shown great promise in the detection and monitoring of neurologic pathologies such as tumor. A necessary component of data processing includes the quantitation of each metabolite, typically done through fitting a model of the spectr...
Humans Neural Networks, Computer Databases, Factual Brain Neoplasms Software Echo-Planar Imaging Algorithms Models, Theoretical Artifacts Deep Learning Glioblastoma Brain Mapping Computer Graphics Magnetic Resonance Spectroscopy Signal-To-Noise Ratio User-Computer Interface Choline Creatine Image Processing, Computer-Assisted Aspartic Acid White Matter
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Referenceless distortion correction of gradient-echo echo-planar imaging under inhomogeneous magnetic fields based on a deep convolutional neural network.

Computers in biology and medicine Jul 18, 2018
Single-shot gradient-echo echo-planar imaging (GE-EPI) plays a significant role in applications where high temporal resolution is necessary. However, GE-EPI is susceptible to inhomogeneous magnetic fields that will cause image distortion. Most existi...
Echo-Planar Imaging Neural Networks, Computer Brain Models, Theoretical Phantoms, Imaging Humans
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Single-shot T mapping using overlapping-echo detachment planar imaging and a deep convolutional neural network.

Magnetic resonance in medicine Apr 24, 2018
PURPOSE: An end-to-end deep convolutional neural network (CNN) based on deep residual network (ResNet) was proposed to efficiently reconstruct reliable T mapping from single-shot overlapping-echo detachment (OLED) planar imaging.
Phantoms, Imaging Computer Simulation Echo-Planar Imaging Adult Humans Deep Learning Algorithms Image Processing, Computer-Assisted Brain
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Support vector machine for breast cancer classification using diffusion-weighted MRI histogram features: Preliminary study.

Journal of magnetic resonance imaging : JMRI Oct 16, 2017
BACKGROUND: Diffusion-weighted MRI (DWI) is currently one of the fastest developing MRI-based techniques in oncology. Histogram properties from model fitting of DWI are useful features for differentiation of lesions, and classification can potentiall...
Receptor, ErbB-2 Aged Diffusion Estrogen Receptor alpha Diffusion Magnetic Resonance Imaging Motion Prospective Studies Adult Support Vector Machine Echo-Planar Imaging Image Interpretation, Computer-Assisted Breast Neoplasms Female Breast Humans Middle Aged Reproducibility of Results Image Processing, Computer-Assisted Machine Learning Algorithms
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