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A survey on shape-constraint deep learning for medical image segmentation
Since the advent of U-Net, fully convolutional deep neural networks and ...
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Channel Attention Networks for Robust MR Fingerprinting Matching
Magnetic Resonance Fingerprinting (MRF) enables simultaneous mapping of ...
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Transfer Learning for Electricity Price Forecasting
Electricity price forecasting is an essential task for all the deregulat...
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Deep Learning Based Detection and Correction of Cardiac MR Motion Artefacts During Reconstruction for High-Quality Segmentation
Segmenting anatomical structures in medical images has been successfully...
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Deep Learning Based Detection and Correction of Cardiac MR Motion Artefacts During Reconstruction for High-Quality Segmentatio
Segmenting anatomical structures in medical images has been successfully...
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A Topological Loss Function for Deep-Learning based Image Segmentation using Persistent Homology
We introduce a method for training neural networks to perform image or v...
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dAUTOMAP: decomposing AUTOMAP to achieve scalability and enhance performance
AUTOMAP is a promising generalized reconstruction approach, however, it ...
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Assessing the Impact of Blood Pressure on Cardiac Function Using Interpretable Biomarkers and Variational Autoencoders
Maintaining good cardiac function for as long as possible is a major con...
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Global and Local Interpretability for Cardiac MRI Classification
Deep learning methods for classifying medical images have demonstrated i...
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Mechanically Powered Motion Imaging Phantoms: Proof of Concept
Motion imaging phantoms are expensive, bulky and difficult to transport ...
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Explicit topological priors for deep-learning based image segmentation using persistent homology
We present a novel method to explicitly incorporate topological prior kn...
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Magnetic Resonance Fingerprinting using Recurrent Neural Networks
Magnetic Resonance Fingerprinting (MRF) is a new approach to quantitativ...
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Deep Learning using K-space Based Data Augmentation for Automated Cardiac MR Motion Artefact Detection
Quality assessment of medical images is essential for complete automatio...
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