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11/09/2022
Automated MRI Field of View Prescription from Region of Interest Prediction by Intra-stack Attention Neural Network
Manual prescription of the field of view (FOV) by MRI technologists is v...
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07/18/2022
GLEAM: Greedy Learning for Large-Scale Accelerated MRI Reconstruction
Unrolled neural networks have recently achieved state-of-the-art acceler...
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11/06/2021
Artifact- and content-specific quality assessment for MRI with image rulers
In clinical practice MR images are often first seen by radiologists long...
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09/30/2021
Noise2Recon: A Semi-Supervised Framework for Joint MRI Reconstruction and Denoising
Deep learning (DL) has shown promise for faster, high quality accelerate...
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08/29/2020
Unsupervised MRI Reconstruction with Generative Adversarial Networks
Deep learning-based image reconstruction methods have achieved promising...
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07/10/2020
Multi-Domain Image Completion for Random Missing Input Data
Multi-domain data are widely leveraged in vision applications taking adv...
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04/03/2020
Complex-Valued Convolutional Neural Networks for MRI Reconstruction
Many real-world signal sources are complex-valued, having real and imagi...
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12/05/2019
Diagnostic Image Quality Assessment and Classification in Medical Imaging: Opportunities and Challenges
Magnetic Resonance Imaging (MRI) suffers from several artifacts, the mos...
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10/15/2019
Wasserstein GANs for MR Imaging: from Paired to Unpaired Training
Lack of ground-truth MR images (labels) impedes the common supervised tr...
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03/19/2019
Compressed Sensing: From Research to Clinical Practice with Data-Driven Learning
Compressed sensing in MRI enables high subsampling factors while maintai...
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05/08/2018
Highly Scalable Image Reconstruction using Deep Neural Networks with Bandpass Filtering
To increase the flexibility and scalability of deep neural networks for ...
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05/31/2017
