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Machine Learning for Medical Image Reconstruction

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Cover of 'Machine Learning for Medical Image Reconstruction'

Table of Contents

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    Book Overview
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    Chapter 1 Deep Learning Super-Resolution Enables Rapid Simultaneous Morphological and Quantitative Magnetic Resonance Imaging
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    Chapter 2 ETER-net: End to End MR Image Reconstruction Using Recurrent Neural Network
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    Chapter 3 Cardiac MR Motion Artefact Correction from K-space Using Deep Learning-Based Reconstruction
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    Chapter 4 Complex Fully Convolutional Neural Networks for MR Image Reconstruction
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    Chapter 5 Magnetic Resonance Fingerprinting Reconstruction via Spatiotemporal Convolutional Neural Networks
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    Chapter 6 Improved Time-Resolved MRA Using k -Space Deep Learning
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    Chapter 7 Joint Motion Estimation and Segmentation from Undersampled Cardiac MR Image
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    Chapter 8 Bayesian Deep Learning for Accelerated MR Image Reconstruction
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    Chapter 9 Sparse-View CT Reconstruction Using Wasserstein GANs
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    Chapter 10 Detecting Anatomical Landmarks for Motion Estimation in Weight-Bearing Imaging of Knees
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    Chapter 11 A U-Nets Cascade for Sparse View Computed Tomography
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    Chapter 12 Approximate k-Space Models and Deep Learning for Fast Photoacoustic Reconstruction
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    Chapter 13 Deep Learning Based Image Reconstruction for Diffuse Optical Tomography
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    Chapter 14 Image Reconstruction via Variational Network for Real-Time Hand-Held Sound-Speed Imaging
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    Chapter 15 Towards Arbitrary Noise Augmentation—Deep Learning for Sampling from Arbitrary Probability Distributions
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    Chapter 16 Left Atria Reconstruction from a Series of Sparse Catheter Paths Using Neural Networks
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    Chapter 17 High Quality Ultrasonic Multi-line Transmission Through Deep Learning
Attention for Chapter 5: Magnetic Resonance Fingerprinting Reconstruction via Spatiotemporal Convolutional Neural Networks
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