
Highly accelerated MR parametric mapping by undersampling the kspace and reducing the contrast number simultaneously with deep learning
Purpose: To propose a novel deep learningbased method called RGNet (re...
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TotalBody LowDose CT Image Denoising using Prior Knowledge Transfer Technique with Contrastive Regularization Mechanism
Reducing the radiation exposure for patients in Totalbody CT scans has ...
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MRI Reconstruction Using Deep EnergyBased Model
Purpose: Although recent deep energybased generative models (EBMs) have...
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MPI: Multireceptive and Parallel Integration for Salient Object Detection
The semantic representation of deep features is essential for image cont...
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Domain Generalization on Medical Imaging Classification using Episodic Training with Task Augmentation
Medical imaging datasets usually exhibit domain shift due to the variati...
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Active Terahertz Imaging Dataset for Concealed Object Detection
Concealed object detection in Terahertz imaging is an urgent need for pu...
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SRRNet: A SuperResolutionInvolved Reconstruction Method for High Resolution MR Imaging
Improving the image resolution and acquisition speed of magnetic resonan...
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Learning CalibratedGuidance for Object Detection in Aerial Images
Recently, the study on object detection in aerial images has made tremen...
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Deep Lowrank plus Sparse Network for Dynamic MR Imaging
In dynamic MR imaging, L+S decomposition, or robust PCA equivalently, ha...
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Homotopic Gradients of Generative Density Priors for MR Image Reconstruction
Deep learning, particularly the generative model, has demonstrated treme...
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Deep Lowrank Prior in Dynamic MR Imaging
The deep learning methods have achieved attractive results in dynamic MR...
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MBARainGAN: Multibranch Attention Generative Adversarial Network for Mixture of Rain Removal from Single Images
Rain severely hampers the visibility of scene objects when images are ca...
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Cooccurrence Background Model with Superpixels for Robust Background Initialization
Background initialization is an important step in many highlevel applic...
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Deep Learning for Highly Accelerated Diffusion Tensor Imaging
Diffusion tensor imaging (DTI) is widely used to examine the human brain...
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An Unsupervised Deep Learning Method for Parallel Cardiac MRI via TimeInterleaved Sampling
Deep learning has achieved good success in cardiac magnetic resonance im...
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Learning Priors in Highfrequency Domain for Inverse Imaging Reconstruction
Illposed inverse problems in imaging remain an active research topic in...
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IFRNet: Iterative Feature Refinement Network for Compressed Sensing MRI
To improve the compressive sensing MRI (CSMRI) approaches in terms of f...
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Denoising Autoencoding Priors in Undecimated Wavelet Domain for MR Image Reconstruction
Compressive sensing is an impressive approach for fast MRI. It aims at r...
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Model Learning: Primal Dual Networks for Fast MR imaging
Magnetic resonance imaging (MRI) is known to be a slow imaging modality ...
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Deep MRI Reconstruction: Unrolled Optimization Algorithms Meet Neural Networks
Image reconstruction from undersampled kspace data has been playing an ...
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Modelbased Deep MR Imaging: the roadmap of generalizing compressed sensing model using deep learning
Accelerating magnetic resonance imaging (MRI) has been an ongoing resear...
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DeepcomplexMRI: Exploiting deep residual network for fast parallel MR imaging with complex convolution
This paper proposes a multichannel image reconstruction method, named D...
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CRDN: Cascaded Residual Dense Networks for Dynamic MR Imaging with Edgeenhanced Loss Constraint
Dynamic magnetic resonance (MR) imaging has generated great research int...
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PCGAN: PartitionControlled Human Image Generation
Human image generation is a very challenging task since it is affected b...
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DIMENSION: Dynamic MR Imaging with Both Kspace and Spatial Prior Knowledge Obtained via MultiSupervised Network Training
Dynamic MR image reconstruction from incomplete kspace data has generat...
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Leveraging Elastic Demand for Forecasting
Demand variance can result in a mismatch between planned supply and actu...
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Improvements and Experiments of a Compact Statistical Background Model
Change detection plays an important role in most videobased application...
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Dong Liang
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