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Low-Dose CT Image Denoising Using a Generative Adversarial Network With Wasserstein Distance and Perceptual Loss

https://doi.org/10.1109/tmi.2018.2827462
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Machine learning will transform radiology significantly within the next 5 years
inferredcites →https://doi.org/10.1002/mp.12344openalex-snapshot
A deep convolutional neural network using directional wavelets for low‐dose X‐ray CT reconstruction
inferredcites →https://doi.org/10.1007/978-3-319-24574-4_28openalex-snapshot
U-Net: Convolutional Networks for Biomedical Image Segmentation
inferredcites →https://doi.org/10.1007/978-3-319-46454-1_36openalex-snapshot
Generative Visual Manipulation on the Natural Image Manifold
inferredcites →https://doi.org/10.1007/978-3-319-46475-6_43openalex-snapshot
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
inferredcites →https://doi.org/10.1007/978-3-319-66179-7_48openalex-snapshot
Medical Image Synthesis with Context-Aware Generative Adversarial Networks
inferredcites →https://doi.org/10.1007/978-3-658-40442-0_9openalex-snapshot
Generative Adversarial Nets
inferredcites →https://doi.org/10.1016/c2009-0-25049-5openalex-snapshot
Feature Extraction and Image Processing
inferredcites →https://doi.org/10.1016/j.ejmp.2012.01.003openalex-snapshot
Iterative reconstruction methods in X-ray CT
inferredcites →https://doi.org/10.1016/s0140-6736(04)15433-0openalex-snapshot
Risk of cancer from diagnostic X-rays: estimates for the UK and 14 other countries
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Computed Tomography — An Increasing Source of Radiation Exposure
inferredcites →https://doi.org/10.1088/0031-9155/49/11/024openalex-snapshot
Distance-driven projection and backprojection in three dimensions
inferredcites →https://doi.org/10.1088/0031-9155/53/17/021openalex-snapshot
Image reconstruction in circular cone-beam computed tomography by constrained, total-variation minimization
inferredcites →https://doi.org/10.1088/0031-9155/55/18/009openalex-snapshot
Block matching 3D random noise filtering for absorption optical projection tomography
inferredcites →https://doi.org/10.1088/0031-9155/56/18/011openalex-snapshot
Low-dose CT reconstruction via edge-preserving total variation regularization
inferredcites →https://doi.org/10.1088/0031-9155/57/23/7923openalex-snapshot
Adaptive-weighted total variation minimization for sparse data toward low-dose x-ray computed tomography image reconstruction
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Improving abdomen tumor low-dose CT images using a fast dictionary learning based processing
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Penalized weighted least-squares image reconstruction for dual energy X-ray transmission tomography
inferredcites →https://doi.org/10.1109/42.993128openalex-snapshot
Statistical image reconstruction for polyenergetic X-ray computed tomography
inferredcites →https://doi.org/10.1109/access.2016.2624938openalex-snapshot
A Perspective on Deep Imaging
inferredcites →https://doi.org/10.1109/cvpr.2009.5206848openalex-snapshot
ImageNet: A large-scale hierarchical image database
inferredcites →https://doi.org/10.1109/cvpr.2017.19openalex-snapshot
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
inferredcites →https://doi.org/10.1109/cvpr.2017.632openalex-snapshot
Image-to-Image Translation with Conditional Adversarial Networks
inferredcites →https://doi.org/10.1109/isbi.2017.7950488openalex-snapshot
Low-dose CT denoising with convolutional neural network
inferredcites →https://doi.org/10.1109/tmi.2006.882141openalex-snapshot
Penalized weighted least-squares approach to sinogram noise reduction and image reconstruction for low-dose X-ray computed tomography
inferredcites →https://doi.org/10.1109/tmi.2011.2175233openalex-snapshot
A Splitting-Based Iterative Algorithm for Accelerated Statistical X-Ray CT Reconstruction
inferredcites →https://doi.org/10.1109/tmi.2012.2195669openalex-snapshot
Low-Dose X-ray CT Reconstruction via Dictionary Learning
inferredcites →https://doi.org/10.1109/tmi.2016.2600249openalex-snapshot
Tensor-Based Dictionary Learning for Spectral CT Reconstruction
inferredcites →https://doi.org/10.1109/tmi.2017.2708987openalex-snapshot
Generative Adversarial Networks for Noise Reduction in Low-Dose CT
inferredcites →https://doi.org/10.1109/tmi.2017.2715284openalex-snapshot
Low-Dose CT With a Residual Encoder-Decoder Convolutional Neural Network
inferredcites →https://doi.org/10.1109/tmi.2017.2785879openalex-snapshot
DAGAN: Deep De-Aliasing Generative Adversarial Networks for Fast Compressed Sensing MRI Reconstruction
inferredcites →https://doi.org/10.1109/tpami.2015.2439281openalex-snapshot
Image Super-Resolution Using Deep Convolutional Networks
inferredcites →https://doi.org/10.1117/12.2006907openalex-snapshot
Image denoising of low-radiation dose coronary CT angiography by an adaptive block-matching 3D algorithm
inferredcites →https://doi.org/10.1117/12.595662openalex-snapshot
Sinogram noise reduction for low-dose CT by statistics-based nonlinear filters
inferredcites →https://doi.org/10.1118/1.2230762openalex-snapshot
Properties of preprocessed sinogram data in x-ray computed tomography
inferredcites →https://doi.org/10.1118/1.3232004openalex-snapshot
Projection space denoising with bilateral filtering and CT noise modeling for dose reduction in CT
inferredcites →https://doi.org/10.1118/1.3638125openalex-snapshot
Low-dose computed tomography image restoration using previous normal-dose scan
inferredcites →https://doi.org/10.1364/josaa.7.001834openalex-snapshot
Multidimensional digital image representations using generalized Kaiser–Bessel window functions
inferredcites →https://doi.org/10.2214/ajr.09.2397openalex-snapshot
Iterative Reconstruction Technique for Reducing Body Radiation Dose at CT: Feasibility Study
inferredcites →https://doi.org/10.3156/jsoft.29.5_177_2openalex-snapshot
GAN（Generative Adversarial Nets）
inferredcites →https://doi.org/10.3389/frobt.2015.00036openalex-snapshot
A Taxonomy of Deep Convolutional Neural Nets for Computer Vision
inferredcites →https://doi.org/10.48550/arxiv.1409.1556openalex-snapshot
Very Deep Convolutional Networks for Large-Scale Image Recognition
inferredcites →https://doi.org/10.48550/arxiv.1412.6980openalex-snapshot
Adam: A Method for Stochastic Optimization
inferredcites →https://doi.org/10.48550/arxiv.1603.04467openalex-snapshot
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
inferredcites →https://doi.org/10.48550/arxiv.1609.07093openalex-snapshot
Neural Photo Editing with Introspective Adversarial Networks
inferredcites →https://doi.org/10.48550/arxiv.1701.00160openalex-snapshot
NIPS 2016 Tutorial: Generative Adversarial Networks
inferredcites →https://doi.org/10.48550/arxiv.1701.07875openalex-snapshot
Wasserstein GAN
inferredcites →https://doi.org/10.48550/arxiv.1704.00028openalex-snapshot
Improved Training of Wasserstein GANs
inferredcites →https://doi.org/10.48550/arxiv.1705.07137openalex-snapshot
Deep De-Aliasing for Fast Compressive Sensing MRI

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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M3S-Net: Multi-Modality Multi-Branch Multi-Self-Attention Network with Structure-Promoting Loss for Low-Dose PET/CT Reconstruction
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Toward a Dual Dose Reduction Strategy of a Total-Body PET/CT System for Attenuation-Corrected PET Imaging via Deep Learning
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Robust contour propagation using deep learning and image registration for online adaptive proton therapy of prostate cancer
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Ultra‐low‐dose PET reconstruction using generative adversarial network with feature matching and task‐specific perceptual loss
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Incorporation of residual attention modules into two neural networks for low‐dose CT denoising
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Noise2Context: Context‐assisted learning 3D thin‐layer for low‐dose CT
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Low‐dose CT denoising via convolutional neural network with an observer loss function
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Deep learning enabled ultra‐fast‐pitch acquisition in clinical X‐ray computed tomography
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A deep learning method for eliminating head motion artifacts in computed tomography
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Reconstruction of three‐dimensional tomographic patient models for radiation dose modulation in CT from two scout views using deep learning
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High‐fidelity fast volumetric brain MRI using synergistic wave‐controlled aliasing in parallel imaging and a hybrid denoising generative adversarial network (HDnGAN)
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Convolutional neural network–based metal and streak artifacts reduction in dental CT images with sparse‐view sampling scheme
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Utilization of an attentive map to preserve anatomical features for training convolutional neural‐network‐based low‐dose CT denoiser
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Physics‐constrained dual‐domain network for CBCT reconstruction from orthogonal X‐rays in gynecologic radiotherapy
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MRI denoising with a non‐blind deep complex‐valued convolutional neural network
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Sparse-View CT Reconstruction Using Wasserstein GANs
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Generating Highly Realistic Images of Skin Lesions with GANs
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Generative Adversarial Networks for Robust Cryo-EM Image Denoising
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Learned Iterative Reconstruction
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Stereo-Correlation and Noise-Distribution Aware ResVoxGAN for Dense Slices Reconstruction and Noise Reduction in Thick Low-Dose CT
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Synthesize Mammogram from Digital Breast Tomosynthesis with Gradient Guided cGANs
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Data Consistent Artifact Reduction for Limited Angle Tomography with Deep Learning Prior
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Measuring CT Reconstruction Quality with Deep Convolutional Neural Networks
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Memory Network-Based Quality Normalization of Magnetic Resonance Images for Brain Segmentation
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Combining Multi-level Loss for Image Denoising
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Medical Image Data Upscaling with Generative Adversarial Networks
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JBFnet - Low Dose CT Denoising by Trainable Joint Bilateral Filtering
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Medical Imaging and Artificial Intelligence
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Low-Dose CT Image Blind Denoising with Graph Convolutional Networks
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Session Based Recommendations Using Recurrent Neural Networks - Long Short-Term Memory
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Overview of Deep Machine Learning Methods
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Uncertainty-Guided Progressive GANs for Medical Image Translation
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Task-Oriented Low-Dose CT Image Denoising
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Improving Generalizability in Limited-Angle CT Reconstruction with Sinogram Extrapolation
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TED-Net: Convolution-Free T2T Vision Transformer-Based Encoder-Decoder Dilation Network for Low-Dose CT Denoising
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Window-Level Is a Strong Denoising Surrogate
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Session Based Recommendations Using Char-Level Recurrent Neural Networks
inferred← citeshttps://doi.org/10.1007/978-3-030-92087-6_17openalex-snapshot
Radiation Dose Optimization: The Role of Artificial Intelligence
inferred← citeshttps://doi.org/10.1007/978-3-030-96285-2_1openalex-snapshot
Material Decomposition and Post-processing: History and Basic Principles
inferred← citeshttps://doi.org/10.1007/978-3-030-98661-2_126openalex-snapshot
Generative Adversarial Networks for Robust Cryo-EM Image Denoising
inferred← citeshttps://doi.org/10.1007/978-3-030-98661-2_67openalex-snapshot
Learned Iterative Reconstruction
inferred← citeshttps://doi.org/10.1007/978-3-031-12053-4_35openalex-snapshot
A Deep Generative Model of Neonatal Cortical Surface Development
inferred← citeshttps://doi.org/10.1007/978-3-031-13841-6_36openalex-snapshot
EEG Generation of Virtual Channels Using an Improved Wasserstein Generative Adversarial Networks
inferred← citeshttps://doi.org/10.1007/978-3-031-16446-0_52openalex-snapshot
Low-Dose CT Reconstruction via Dual-Domain Learning and Controllable Modulation
inferred← citeshttps://doi.org/10.1007/978-3-031-16446-0_56openalex-snapshot
Analyzing and Improving Low Dose CT Denoising Network via HU Level Slicing
inferred← citeshttps://doi.org/10.1007/978-3-031-16446-0_60openalex-snapshot
Patch-Wise Deep Metric Learning for Unsupervised Low-Dose CT Denoising
inferred← citeshttps://doi.org/10.1007/978-3-031-16446-0_64openalex-snapshot
MRI Reconstruction by Completing Under-sampled K-space Data with Learnable Fourier Interpolation
inferred← citeshttps://doi.org/10.1007/978-3-031-16446-0_75openalex-snapshot
A Transformer-Based Iterative Reconstruction Model for Sparse-View CT Reconstruction
inferred← citeshttps://doi.org/10.1007/978-3-031-16525-2_11openalex-snapshot
Intra-operative OCT (iOCT) Super Resolution: A Two-Stage Methodology Leveraging High Quality Pre-operative OCT Scans
inferred← citeshttps://doi.org/10.1007/978-3-031-17247-2_13openalex-snapshot
DPDudoNet: Deep-Prior Based Dual-Domain Network for Low-Dose Computed Tomography Reconstruction
inferred← citeshttps://doi.org/10.1007/978-3-031-17247-2_14openalex-snapshot
MTD-GAN: Multi-task Discriminator Based Generative Adversarial Networks for Low-Dose CT Denoising
inferred← citeshttps://doi.org/10.1007/978-3-031-17247-2_9openalex-snapshot
DuDoTrans: Dual-Domain Transformer for Sparse-View CT Reconstruction
inferred← citeshttps://doi.org/10.1007/978-3-031-22695-3_3openalex-snapshot
Diverse Audio-to-Video GAN using Multiscale Image Fusion
inferred← citeshttps://doi.org/10.1007/978-3-031-25066-8_29openalex-snapshot
Beyond Local Processing: Adapting CNNs for CT Reconstruction
inferred← citeshttps://doi.org/10.1007/978-3-031-29313-9_4openalex-snapshot
Unsupervising Denoising Model Based Generative Adversarial Networks
inferred← citeshttps://doi.org/10.1007/978-3-031-30111-7_47openalex-snapshot
Low Dose CT Image Denoising Using Efficient Transformer with SimpleGate Mechanism
inferred← citeshttps://doi.org/10.1007/978-3-031-43827-1_18openalex-snapshot
Deep Learning in Image Processing: Part 2—Image Enhancement, Reconstruction and Registration
inferred← citeshttps://doi.org/10.1007/978-3-031-43907-0_23openalex-snapshot
Inter-slice Consistency for Unpaired Low-Dose CT Denoising Using Boosted Contrastive Learning
inferred← citeshttps://doi.org/10.1007/978-3-031-43990-2_39openalex-snapshot
CTFlow: Mitigating Effects of Computed Tomography Acquisition and Reconstruction with Normalizing Flows
inferred← citeshttps://doi.org/10.1007/978-3-031-43999-5_34openalex-snapshot
ASCON: Anatomy-Aware Supervised Contrastive Learning Framework for Low-Dose CT Denoising
inferred← citeshttps://doi.org/10.1007/978-3-031-48593-0_5openalex-snapshot
BliMSR: Blind Degradation Modelling for Generating High-Resolution Medical Images
inferred← citeshttps://doi.org/10.1007/978-3-031-72104-5_58openalex-snapshot
Region Attention Transformer for Medical Image Restoration
inferred← citeshttps://doi.org/10.1007/978-3-031-73039-9_26openalex-snapshot
Domain Generalization of 3D Object Detection by Density-Resampling
inferred← citeshttps://doi.org/10.1007/978-3-031-75653-5_1openalex-snapshot
Deep Learning Techniques for CT Image Denoising and Resolution Enhancement
inferred← citeshttps://doi.org/10.1007/978-3-031-75653-5_2openalex-snapshot
Physically Interpretable Deep Learning Reconstruction for Photon Counting Spectral CT
inferred← citeshttps://doi.org/10.1007/978-3-031-92808-6_18openalex-snapshot
Khattat: Enhancing Readability and Concept Representation of Semantic Typography
inferred← citeshttps://doi.org/10.1007/978-3-031-94802-2_10openalex-snapshot
Prior-Guided Image Denoising via Generative Adversarial Networks with Single Noisy Images
inferred← citeshttps://doi.org/10.1007/978-3-032-04947-6_15openalex-snapshot
DCT-Net: Dual-Branch CT Reconstruction from Orthogonal X-Rays with Diffusion Model and Contrastive Learning
inferred← citeshttps://doi.org/10.1007/978-3-032-05169-1_64openalex-snapshot
VisNet: A Human Visual System Inspired Lightweight Dual-Path Network for Medical Images Denoising
inferred← citeshttps://doi.org/10.1007/978-3-032-08384-5_31openalex-snapshot
Toward Better Optimization of Low-Dose CT Enhancement: A Critical Analysis of Loss Functions and Image Quality Assessment Metrics
inferred← citeshttps://doi.org/10.1007/978-3-032-13654-1_23openalex-snapshot
AST-n: A Fast Sampling Approach for Low-Dose CT Reconstruction Using Diffusion Models
inferred← citeshttps://doi.org/10.1007/978-3-032-27160-0_14openalex-snapshot
Designing Wavelet-Guided Denoising of Low-Dose CT Scans Using a Frequency-Domain Cross-Attention UNet Architecture
inferred← citeshttps://doi.org/10.1007/978-3-032-39898-7_40openalex-snapshot
Anatomical Mask Conditioning for Low-Dose CT Denoising: An Architecture-Focused Investigation
inferred← citeshttps://doi.org/10.1007/978-3-319-94878-2_13openalex-snapshot
Cardiovascular Diseases
inferred← citeshttps://doi.org/10.1007/978-3-319-96029-6_2openalex-snapshot
Sparsity-Based Denoising of Photographic Images: From Model-Based to Data-Driven
inferred← citeshttps://doi.org/10.1007/978-981-13-6052-7_1openalex-snapshot
Enhanced Medical Image De-noising Using Auto Encoders and MLP
inferred← citeshttps://doi.org/10.1007/978-981-15-4288-6_5openalex-snapshot
Image Denoising Using Generative Adversarial Network
inferred← citeshttps://doi.org/10.1007/978-981-15-8450-3_58openalex-snapshot
Low-Dose CT Image Denoising Using a Generative Adversarial Network Based on U-Net Network Structure
inferred← citeshttps://doi.org/10.1007/978-981-15-9492-2_10openalex-snapshot
Recent Advancements in Medical Imaging: A Machine Learning Approach
inferred← citeshttps://doi.org/10.1007/978-981-16-0733-2_26openalex-snapshot
Machine Learning Applications for Computer-Aided Medical Diagnostics
inferred← citeshttps://doi.org/10.1007/978-981-19-2130-8_79openalex-snapshot
U-shaped Transformer for Enhancing Low-Dose CT Images
inferred← citeshttps://doi.org/10.1007/978-981-19-5037-7_6openalex-snapshot
Reconstructing Medical Images Using Generative Adversarial Networks: A Study
inferred← citeshttps://doi.org/10.1007/978-981-19-6290-5_9openalex-snapshot
Security Issues in Deep Learning
inferred← citeshttps://doi.org/10.1007/978-981-92-1947-6_35openalex-snapshot
GROFF: A Generative Restoration Model for Occluded Face Filling
inferred← citeshttps://doi.org/10.1007/978-981-95-0568-5_10openalex-snapshot
Brain Imaging and Tissue Segmentation from Paired CT-MRI Labels for Cognitively Normal and Dementia Cohort
inferred← citeshttps://doi.org/10.1007/978-981-95-9504-4_12openalex-snapshot
ELDCNN: Edge Extraction and Large Kernel Attention-Based Dual Convolutional Neural Network for Low-Dose CT Image Denoising
inferred← citeshttps://doi.org/10.1007/978-981-96-5848-0_6openalex-snapshot
Enhancing Image Reconstruction Fidelity in Low-Dose CT Scans: A Comprehensive MPS-UNet Framework
inferred← citeshttps://doi.org/10.1007/978-981-96-6588-4_9openalex-snapshot
CRA-Eformer: Cross-Scale Residual Attention-Based Edge-Guide Transformer for Low-Dose CT Denoising
inferred← citeshttps://doi.org/10.1007/978-981-96-6960-8_7openalex-snapshot
TBED-CNN: Tripartite-Branching Encoder-Decoder CNN for Low-Dose CT Denoising
inferred← citeshttps://doi.org/10.1007/978-981-96-9914-8_36openalex-snapshot
ULTRA-Net: An Efficient and Interpretable Deep Network for Low-Dose CT Images Denoising
inferred← citeshttps://doi.org/10.1007/978-981-97-0641-9_54openalex-snapshot
Residual Learning and Deep Learning Models for Image Denoising in Medical Applications
inferred← citeshttps://doi.org/10.1007/978-981-97-0896-3_8openalex-snapshot
Artificial Intelligence in Healthcare: India Case Study
inferred← citeshttps://doi.org/10.1007/978-981-97-3526-6_7openalex-snapshot
Advancements in CT Image Reconstruction: An Exploration of Conventional and Deep Learning-Driven Approaches
inferred← citeshttps://doi.org/10.1007/978-981-97-4149-6_26openalex-snapshot
Generative Adversarial Networks in Medical Image Analysis: A Comprehensive Survey
inferred← citeshttps://doi.org/10.1007/978-981-97-5345-1_1openalex-snapshot
Artificial Intelligence in Diagnostic Medical Image Processing for Advanced Healthcare Applications
inferred← citeshttps://doi.org/10.1007/978-981-97-5979-8_14openalex-snapshot
Enhancing Low-Dose SPECT 2D Reconstruction from One-Dimensional Projections By Using Conditional Generative Adversarial Networks for Improved Image Quality
inferred← citeshttps://doi.org/10.1007/978-981-97-8533-9_14openalex-snapshot
Dense Net Built on Relying Generative Adversarial Networks for Conceptualizing a Generative Adversarial Network Image Denoising
inferred← citeshttps://doi.org/10.1007/978-981-99-8558-6_40openalex-snapshot
GCUNET: Combining GNN and CNN for Sinogram Restoration in Low-Dose SPECT Reconstruction
inferred← citeshttps://doi.org/10.1007/s00034-022-02084-6openalex-snapshot
A Novel Denoising Method for Medical CT Images Based on Moving Decomposition Framework
inferred← citeshttps://doi.org/10.1007/s00034-023-02575-0openalex-snapshot
Low-Dose CT Image Denoising with a Residual Multi-scale Feature Fusion Convolutional Neural Network and Enhanced Perceptual Loss
inferred← citeshttps://doi.org/10.1007/s00034-023-02594-xopenalex-snapshot
Low-Dose CT Denoising Algorithm Based on Image Cartoon Texture Decomposition
inferred← citeshttps://doi.org/10.1007/s00034-024-02631-3openalex-snapshot
Cartoon-Texture Features Guided Network for Low-Dose CT Denoising
inferred← citeshttps://doi.org/10.1007/s00034-025-03079-9openalex-snapshot
Dynamic Perception-oriented Low-dose CT Image Denoising Network using Structure-aware Self-similarity
inferred← citeshttps://doi.org/10.1007/s00117-019-00621-0openalex-snapshot
Künstliche Intelligenz in der Radiologie
inferred← citeshttps://doi.org/10.1007/s00138-020-01060-xopenalex-snapshot
Deep learning in medical image registration: a survey
inferred← citeshttps://doi.org/10.1007/s00138-021-01240-3openalex-snapshot
Integration of 2D iteration and a 3D CNN-based model for multi-type artifact suppression in C-arm cone-beam CT
inferred← citeshttps://doi.org/10.1007/s00138-024-01568-6openalex-snapshot
MDUNet: deep-prior unrolling network with multi-parameter data integration for low-dose computed tomography reconstruction
inferred← citeshttps://doi.org/10.1007/s00256-021-03876-8openalex-snapshot
AI musculoskeletal clinical applications: how can AI increase my day-to-day efficiency?
inferred← citeshttps://doi.org/10.1007/s00330-019-06183-yopenalex-snapshot
Deep learning–based image restoration algorithm for coronary CT angiography
inferred← citeshttps://doi.org/10.1007/s00330-020-07225-6openalex-snapshot
Ultra-low-dose chest CT imaging of COVID-19 patients using a deep residual neural network
inferred← citeshttps://doi.org/10.1007/s00330-021-07714-2openalex-snapshot
Contrast agent dose reduction in computed tomography with deep learning using a conditional generative adversarial network
inferred← citeshttps://doi.org/10.1007/s00330-021-08199-9openalex-snapshot
Dose reduction potential of vendor-agnostic deep learning model in comparison with deep learning–based image reconstruction algorithm on CT: a phantom study
inferred← citeshttps://doi.org/10.1007/s00330-022-08638-1openalex-snapshot
Accelerating susceptibility-weighted imaging with deep learning by complex-valued convolutional neural network (ComplexNet): validation in clinical brain imaging
inferred← citeshttps://doi.org/10.1007/s00330-022-08971-5openalex-snapshot
Motion artifact removal in coronary CT angiography based on generative adversarial networks
inferred← citeshttps://doi.org/10.1007/s00330-022-08975-1openalex-snapshot
Artificial intelligence–based full aortic CT angiography imaging with ultra-low-dose contrast medium: a preliminary study
inferred← citeshttps://doi.org/10.1007/s00371-020-01996-1openalex-snapshot
Low-dose CT lung images denoising based on multiscale parallel convolution neural network
inferred← citeshttps://doi.org/10.1007/s00371-021-02341-wopenalex-snapshot
Low-dose CT image restoration based on noise prior regression network
inferred← citeshttps://doi.org/10.1007/s00371-022-02599-8openalex-snapshot
Unpaired low-dose CT denoising via an improved cycle-consistent adversarial network with attention ensemble
inferred← citeshttps://doi.org/10.1007/s00500-020-05013-4openalex-snapshot
RecDNN: deep neural network for image reconstruction from limited view projection data
inferred← citeshttps://doi.org/10.1007/s00500-021-05870-7openalex-snapshot
Pyramidal convolution attention generative adversarial network with data augmentation for image denoising
inferred← citeshttps://doi.org/10.1007/s00500-023-07883-wopenalex-snapshot
Offline handwritten Tai Le character recognition using wavelet deep convolution features and ensemble deep variationally sparse Gaussian processes
inferred← citeshttps://doi.org/10.1007/s00521-018-04007-6openalex-snapshot
Removing ring artifacts in CBCT images via generative adversarial networks with unidirectional relative total variation loss
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