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Projection-Based cascaded U-Net model for MR image reconstruction
Amir Aghabiglou,
Ender M. Eksioglu
*
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Corresponding author for this work
Department of Electronics and Communication Engineering
Istanbul Technical University
Research output
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Contribution to journal
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Article
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peer-review
21
Citations (Scopus)
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Keyphrases
Aliasing Artifacts
8%
Annotated Dataset
8%
Biomedical Images
8%
Cascade Framework
8%
Cascade Structure
8%
Cascaded CNN
8%
Data Acquisition Time
8%
Data Consistency
25%
Deep Learning
16%
Deep Model
8%
Deep Network
16%
Effective Network
8%
Fast MRI
16%
Imaging Inverse Problems
8%
Inverse Problem
8%
K-space
8%
K-Space Data
8%
Learning Implementation
8%
Magnetic Resonance Image Reconstruction
8%
Magnetic Resonance Imaging
8%
MR Image Reconstruction
100%
MRI Reconstruction
16%
Network Structure
8%
Projection-based
100%
PyTorch
8%
Reconstruction Method
8%
Reconstruction Performance
16%
Reconstruction Problem
8%
Reconstruction Process
8%
Segmentation Problem
8%
U-Net
100%
Undersampling
16%
Updated Data
16%
Engineering
Acquisition Time
33%
Convolutional Neural Network
100%
Data Collection
33%
Deep Learning Method
66%
Image Reconstruction
100%
Net Structure
100%
Reconstruction Problem
33%
Simulation Result
33%
Space Data
33%
Computer Science
Acquisition Time
8%
Aliasing Artifact
8%
Conventional Data
8%
Convolutional Neural Network
25%
Data Collection
8%
Data Consistency
25%
Deep Learning Method
16%
Image Reconstruction
100%
Inverse Problem
16%
Network Structures
8%
Reconstruction Problem
8%
Reconstruction Process
8%
Speed-up
8%
U-Net
100%
Physics
Convolutional Neural Network
100%
Data Acquisition
33%
Deep Learning Method
66%
Image Reconstruction
100%
Magnetic Resonance
33%
Earth and Planetary Sciences
Data Acquisition
33%
Image Reconstruction
100%
Inverse Problem
66%