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02/18/2023
Dual-Domain Self-Supervised Learning for Accelerated Non-Cartesian MRI Reconstruction
While enabling accelerated acquisition and improved reconstruction accur...
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06/27/2022
ContraReg: Contrastive Learning of Multi-modality Unsupervised Deformable Image Registration
Establishing voxelwise semantic correspondence across distinct imaging m...
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01/26/2022
DSFormer: A Dual-domain Self-supervised Transformer for Accelerated Multi-contrast MRI Reconstruction
Multi-contrast MRI (MC-MRI) captures multiple complementary imaging moda...
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07/12/2020
Deep Network Interpolation for Accelerated Parallel MR Image Reconstruction
We present a deep network interpolation strategy for accelerated paralle...
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12/18/2019
Σ-net: Systematic Evaluation of Iterative Deep Neural Networks for Fast Parallel MR Image Reconstruction
Purpose: To systematically investigate the influence of various data con...
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12/11/2019
Σ-net: Ensembled Iterative Deep Neural Networks for Accelerated Parallel MR Image Reconstruction
We explore an ensembled Σ-net for fast parallel MR imaging, including pa...
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09/25/2019
Data consistency networks for (calibration-less) accelerated parallel MR image reconstruction
We present simple reconstruction networks for multi-coil data by extendi...
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09/24/2019
dAUTOMAP: decomposing AUTOMAP to achieve scalability and enhance performance
AUTOMAP is a promising generalized reconstruction approach, however, it ...
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08/20/2019
Joint Motion Estimation and Segmentation from Undersampled Cardiac MR Image
Accelerating the acquisition of magnetic resonance imaging (MRI) is a ch...
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08/20/2019
Unsupervised Multi-modal Style Transfer for Cardiac MR Segmentation
In this work, we present a fully automatic method to segment cardiac str...
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07/22/2019
k-t NEXT: Dynamic MR Image Reconstruction Exploiting Spatio-temporal Correlations
Dynamic magnetic resonance imaging (MRI) exhibits high correlations in k...
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07/19/2019
VS-Net: Variable splitting network for accelerated parallel MRI reconstruction
In this work, we propose a deep learning approach for parallel magnetic ...
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02/11/2019
Deep Hashing using Entropy Regularised Product Quantisation Network
In large scale systems, approximate nearest neighbour search is a crucia...
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08/26/2018
Automatic 3D bi-ventricular segmentation of cardiac images by a shape-constrained multi-task deep learning approach
Deep learning approaches have achieved state-of-the-art performance in c...
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08/22/2018
Attention Gated Networks: Learning to Leverage Salient Regions in Medical Images
We propose a novel attention gate (AG) model for medical image analysis ...
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07/27/2018
Deep nested level sets: Fully automated segmentation of cardiac MR images in patients with pulmonary hypertension
In this paper we introduce a novel and accurate optimisation method for ...
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06/28/2018
Adversarial and Perceptual Refinement for Compressed Sensing MRI Reconstruction
Deep learning approaches have shown promising performance for compressed...
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06/11/2018
Joint Learning of Motion Estimation and Segmentation for Cardiac MR Image Sequences
Cardiac motion estimation and segmentation play important roles in quant...
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05/30/2018
Stochastic Deep Compressive Sensing for the Reconstruction of Diffusion Tensor Cardiac MRI
Understanding the structure of the heart at the microscopic scale of car...
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04/15/2018
Attention-Gated Networks for Improving Ultrasound Scan Plane Detection
In this work, we apply an attention-gated network to real-time automated...
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04/11/2018
Attention U-Net: Learning Where to Look for the Pancreas
We propose a novel attention gate (AG) model for medical imaging that au...
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12/05/2017
Convolutional Recurrent Neural Networks for Dynamic MR Image Reconstruction
Accelerating the data acquisition of dynamic magnetic resonance imaging ...
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04/08/2017
A Deep Cascade of Convolutional Neural Networks for Dynamic MR Image Reconstruction
Inspired by recent advances in deep learning, we propose a framework for...
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03/01/2017
