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04/11/2023
SPIRiT-Diffusion: Self-Consistency Driven Diffusion Model for Accelerated MRI
Diffusion models are a leading method for image generation and have been...
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11/24/2022
Iterative Data Refinement for Self-Supervised MR Image Reconstruction
Magnetic Resonance Imaging (MRI) has become an important technique in th...
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11/16/2022
Semi-Supervised and Self-Supervised Collaborative Learning for Prostate 3D MR Image Segmentation
Volumetric magnetic resonance (MR) image segmentation plays an important...
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11/16/2022
Uncertainty-Aware Multi-Parametric Magnetic Resonance Image Information Fusion for 3D Object Segmentation
Multi-parametric magnetic resonance (MR) imaging is an indispensable too...
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08/08/2022
SelfCoLearn: Self-supervised collaborative learning for accelerating dynamic MR imaging
Lately, deep learning has been extensively investigated for accelerating...
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08/05/2022
First Glance Diagnosis: Brain Disease Classification with Single fMRI Volume
In neuroimaging analysis, functional magnetic resonance imaging (fMRI) c...
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03/18/2022
Rethinking the optimization process for self-supervised model-driven MRI reconstruction
Recovering high-quality images from undersampled measurements is critica...
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02/03/2022
PARCEL: Physics-based unsupervised contrastive representation learning for parallel MR imaging
With the successful application of deep learning in magnetic resonance i...
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01/08/2022
Expert Knowledge-guided Geometric Representation Learning for Magnetic Resonance Imaging-based Glioma Grading
Radiomics and deep learning have shown high popularity in automatic glio...
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09/26/2021
Self-Supervised Learning for MRI Reconstruction with a Parallel Network Training Framework
Image reconstruction from undersampled k-space data plays an important r...
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12/09/2020
AIDE: Annotation-efficient deep learning for automatic medical image segmentation
Accurate image segmentation is crucial for medical imaging applications....
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11/27/2020
Multi-task MR Imaging with Iterative Teacher Forcing and Re-weighted Deep Learning
Noises, artifacts, and loss of information caused by the magnetic resona...
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08/05/2020
A coarse-to-fine framework for unsupervised multi-contrast MR image deformable registration with dual consistency constraint
Multi-contrast magnetic resonance (MR) image registration is essential i...
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06/22/2020
Deep Low-rank Prior in Dynamic MR Imaging
The deep learning methods have achieved attractive results in dynamic MR...
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12/20/2019
An Unsupervised Deep Learning Method for Parallel Cardiac MRI via Time-Interleaved Sampling
Deep learning has achieved good success in cardiac magnetic resonance im...
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08/24/2019
LANTERN: learn analysis transform network for dynamic magnetic resonance imaging with small dataset
This paper proposes to learn analysis transform network for dynamic magn...
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08/06/2019
Learning Cross-Modal Deep Representations for Multi-Modal MR Image Segmentation
Multi-modal magnetic resonance imaging (MRI) is essential in clinics for...
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07/16/2019
CLCI-Net: Cross-Level fusion and Context Inference Networks for Lesion Segmentation of Chronic Stroke
Segmenting stroke lesions from T1-weighted MR images is of great value f...
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06/11/2019
DeepcomplexMRI: Exploiting deep residual network for fast parallel MR imaging with complex convolution
This paper proposes a multi-channel image reconstruction method, named D...
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01/18/2019
CRDN: Cascaded Residual Dense Networks for Dynamic MR Imaging with Edge-enhanced Loss Constraint
Dynamic magnetic resonance (MR) imaging has generated great research int...
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09/30/2018
DIMENSION: Dynamic MR Imaging with Both K-space and Spatial Prior Knowledge Obtained via Multi-Supervised Network Training
Dynamic MR image reconstruction from incomplete k-space data has generat...
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09/21/2018