{"total":162,"rows":[{"id":"2207.08208","title":"Unsupervised Medical Image Translation with Adversarial Diffusion Models","created":"2022-07-17","cited_by_count":192,"area":"diffusion"},{"id":"2103.14756","title":"Equivariant Imaging: Learning Beyond the Range Space","created":"2021-03-26","cited_by_count":83,"area":null},{"id":"2301.03362","title":"Image Denoising: The Deep Learning Revolution and Beyond -- A Survey Paper --","created":"2023-01-09","cited_by_count":71,"area":null},{"id":"2209.12104","title":"Conversion Between CT and MRI Images Using Diffusion and Score-Matching Models","created":"2022-09-24","cited_by_count":69,"area":null},{"id":"2304.01814","title":"CoreDiff: Contextual Error-Modulated Generalized Diffusion Model for Low-Dose CT Denoising and Generalization","created":"2023-04-04","cited_by_count":52,"area":"diffusion"},{"id":"2112.12047","title":"Generating Synthetic Mixed-type Longitudinal Electronic Health Records for Artificial Intelligent Applications","created":"2021-12-22","cited_by_count":47,"area":null},{"id":"2108.10772","title":"DU-GAN: Generative Adversarial Networks with Dual-Domain U-Net Based Discriminators for Low-Dose CT Denoising","created":"2021-08-24","cited_by_count":46,"area":null},{"id":"2202.13517","title":"CTformer: Convolution-free Token2Token Dilated Vision Transformer for Low-dose CT Denoising","created":"2022-02-28","cited_by_count":46,"area":null},{"id":"2304.02742","title":"Zero-shot Medical Image Translation via Frequency-Guided Diffusion Models","created":"2023-04-05","cited_by_count":40,"area":"diffusion"},{"id":"2103.15814","title":"High-Fidelity and Arbitrary Face Editing","created":"2021-03-29","cited_by_count":35,"area":null},{"id":"2109.08044","title":"Eformer: Edge Enhancement based Transformer for Medical Image Denoising","created":"2021-09-16","cited_by_count":30,"area":null},{"id":"2211.13926","title":"Generative Modeling in Sinogram Domain for Sparse-view CT Reconstruction","created":"2022-11-25","cited_by_count":27,"area":"diffusion"},{"id":"2106.04650","title":"TED-net: Convolution-free T2T Vision Transformer-based Encoder-decoder Dilation network for Low-dose CT Denoising","created":"2021-06-08","cited_by_count":21,"area":null},{"id":"2305.15887","title":"Diffusion Probabilistic Priors for Zero-Shot Low-Dose CT Image Denoising","created":"2023-05-25","cited_by_count":21,"area":"diffusion"},{"id":"2202.10847","title":"UncertaINR: Uncertainty Quantification of End-to-End Implicit Neural Representations for Computed Tomography","created":"2022-02-22","cited_by_count":19,"area":null},{"id":"2211.10388","title":"Patch-Based Denoising Diffusion Probabilistic Model for Sparse-View CT Reconstruction","created":"2022-11-18","cited_by_count":18,"area":"diffusion"},{"id":"2312.15663","title":"IQAGPT: Image Quality Assessment with Vision-language and ChatGPT Models","created":"2023-12-25","cited_by_count":18,"area":null},{"id":"2106.15542","title":"Uncertainty-Guided Progressive GANs for Medical Image Translation","created":"2021-06-29","cited_by_count":16,"area":null},{"id":"2108.02160","title":"MRI to PET Cross-Modality Translation using Globally and Locally Aware GAN (GLA-GAN) for Multi-Modal Diagnosis of Alzheimer's Disease","created":"2021-08-04","cited_by_count":16,"area":null},{"id":"2104.08538","title":"Cycle-free CycleGAN using Invertible Generator for Unsupervised Low-Dose CT Denoising","created":"2021-04-17","cited_by_count":15,"area":null},{"id":"2106.03223","title":"Meta-learning with implicit gradients in a few-shot setting for medical image segmentation","created":"2021-06-06","cited_by_count":15,"area":null},{"id":"2307.12225","title":"ASCON: Anatomy-aware Supervised Contrastive Learning Framework for Low-dose CT Denoising","created":"2023-07-23","cited_by_count":15,"area":null},{"id":"2203.15725","title":"Physics-/Model-Based and Data-Driven Methods for Low-Dose Computed Tomography: A survey","created":"2022-03-29","cited_by_count":14,"area":null},{"id":"2206.03709","title":"Hypernetwork-based Personalized Federated Learning for Multi-Institutional CT Imaging","created":"2022-06-08","cited_by_count":14,"area":null},{"id":"2212.10305","title":"Which Pixel to Annotate: a Label-Efficient Nuclei Segmentation Framework","created":"2022-12-20","cited_by_count":14,"area":null},{"id":"2205.08887","title":"3D Segmentation Guided Style-based Generative Adversarial Networks for PET Synthesis","created":"2022-05-18","cited_by_count":13,"area":null},{"id":"2111.10790","title":"DuDoTrans: Dual-Domain Transformer Provides More Attention for Sinogram Restoration in Sparse-View CT Reconstruction","created":"2021-11-21","cited_by_count":12,"area":null},{"id":"2302.10630","title":"LIT-Former: Linking In-plane and Through-plane Transformers for Simultaneous CT Image Denoising and Deblurring","created":"2023-02-21","cited_by_count":12,"area":null},{"id":"2103.13557","title":"Task-Oriented Low-Dose CT Image Denoising","created":"2021-03-25","cited_by_count":11,"area":null},{"id":"2302.04032","title":"A Systematic Performance Analysis of Deep Perceptual Loss Networks: Breaking Transfer Learning Conventions","created":"2023-02-08","cited_by_count":11,"area":null},{"id":"2409.13094","title":"DenoMamba: A fused state-space model for low-dose CT denoising","created":"2024-09-19","cited_by_count":11,"area":null},{"id":"2101.01597","title":"Contextual colorization and denoising for low-light ultra high resolution sequences","created":"2021-01-05","cited_by_count":10,"area":null},{"id":"2201.10345","title":"Ultra Low-Parameter Denoising: Trainable Bilateral Filter Layers in Computed Tomography","created":"2022-01-25","cited_by_count":9,"area":null},{"id":"2208.06643","title":"Recent Progress in Transformer-based Medical Image Analysis","created":"2022-08-13","cited_by_count":9,"area":null},{"id":"2310.06949","title":"Diffusion Prior Regularized Iterative Reconstruction for Low-dose CT","created":"2023-10-10","cited_by_count":9,"area":"diffusion"},{"id":"2103.05255","title":"Improving Generalizability in Limited-Angle CT Reconstruction with Sinogram Extrapolation","created":"2021-03-09","cited_by_count":8,"area":null},{"id":"2208.03934","title":"Inflating 2D Convolution Weights for Efficient Generation of 3D Medical Images","created":"2022-08-08","cited_by_count":8,"area":null},{"id":"2406.16601","title":"Do As I Do: Pose Guided Human Motion Copy","created":"2024-06-24","cited_by_count":8,"area":null},{"id":"2104.08845","title":"Lesion-Inspired Denoising Network: Connecting Medical Image Denoising and Lesion Detection","created":"2021-04-18","cited_by_count":7,"area":null},{"id":"2207.00400","title":"WNet: A data-driven dual-domain denoising model for sparse-view computed tomography with a trainable reconstruction layer","created":"2022-07-01","cited_by_count":7,"area":null},{"id":"2303.12861","title":"Parallel Diffusion Model-based Sparse-view Cone-beam Breast CT","created":"2023-03-22","cited_by_count":7,"area":"diffusion"},{"id":"2403.06128","title":"Low-dose CT Denoising with Language-engaged Dual-space Alignment","created":"2024-03-10","cited_by_count":7,"area":null},{"id":"2504.11286","title":"Lightweight Medical Image Restoration via Integrating Reliable Lesion-Semantic Driven Prior","created":"2025-04-15","cited_by_count":7,"area":null},{"id":"2104.12939","title":"Provably Convergent Learned Inexact Descent Algorithm for Low-Dose CT Reconstruction","created":"2021-04-27","cited_by_count":6,"area":null},{"id":"2111.09539","title":"Deep neural networks-based denoising models for CT imaging and their efficacy","created":"2021-11-18","cited_by_count":6,"area":null},{"id":"2304.05359","title":"A comparative study between paired and unpaired Image Quality Assessment in Low-Dose CT Denoising","created":"2023-04-11","cited_by_count":6,"area":null},{"id":"2310.05237","title":"Latent Diffusion Model for Medical Image Standardization and Enhancement","created":"2023-10-08","cited_by_count":6,"area":"diffusion"},{"id":"2311.10845","title":"Domain Generalization of 3D Object Detection by Density-Resampling","created":"2023-11-17","cited_by_count":6,"area":null},{"id":"2404.03126","title":"GaSpCT: Gaussian Splatting for Novel CT Projection View Synthesis","created":"2024-04-04","cited_by_count":6,"area":null},{"id":"2410.01591","title":"Imaging foundation model for universal enhancement of non-ideal measurement CT","created":"2024-10-02","cited_by_count":6,"area":null},{"id":"2103.14528","title":"Model-based Reconstruction with Learning: From Unsupervised to Supervised and Beyond","created":"2021-03-26","cited_by_count":5,"area":null},{"id":"2104.01592","title":"Synthesizing MR Image Contrast Enhancement Using 3D High-resolution ConvNets","created":"2021-04-04","cited_by_count":5,"area":null},{"id":"2208.04679","title":"Improved Multiple-Image-Based Reflection Removal Algorithm Using Deep Neural Networks","created":"2022-08-09","cited_by_count":5,"area":null},{"id":"2402.08159","title":"PFCM: Poisson flow consistency models for low-dose CT image denoising","created":"2024-02-13","cited_by_count":5,"area":"diffusion"},{"id":"2407.05709","title":"Heterogeneous window transformer for image denoising","created":"2024-07-08","cited_by_count":5,"area":null},{"id":"2407.09268","title":"Region Attention Transformer for Medical Image Restoration","created":"2024-07-12","cited_by_count":5,"area":null},{"id":"2103.06575","title":"An unsupervised deep learning framework for medical image denoising","created":"2021-03-11","cited_by_count":4,"area":null},{"id":"2204.14100","title":"Adversarial Distortion Learning for Medical Image Denoising","created":"2022-04-29","cited_by_count":4,"area":null},{"id":"2303.00212","title":"A task-specific deep-learning-based denoising approach for myocardial perfusion SPECT","created":"2023-03-01","cited_by_count":4,"area":null},{"id":"2308.03354","title":"Energy-Guided Diffusion Model for CBCT-to-CT Synthesis","created":"2023-08-07","cited_by_count":4,"area":"diffusion"},{"id":"2312.09754","title":"PPFM: Image denoising in photon-counting CT using single-step posterior sampling Poisson flow generative models","created":"2023-12-15","cited_by_count":4,"area":"diffusion"},{"id":"2411.07930","title":"CT-Mamba: A Hybrid Convolutional State Space Model for Low-Dose CT Denoising","created":"2024-11-12","cited_by_count":4,"area":"ssm"},{"id":"2101.04793","title":"Generative Adversarial U-Net for Domain-free Medical Image Augmentation","created":"2021-01-12","cited_by_count":3,"area":null},{"id":"2103.12995","title":"MANAS: Multi-Scale and Multi-Level Neural Architecture Search for Low-Dose CT Denoising","created":"2021-03-24","cited_by_count":3,"area":null},{"id":"2104.15050","title":"Generative Models Improve Radiomics Reproducibility in Low Dose CTs: A Simulation Study","created":"2021-04-30","cited_by_count":3,"area":null},{"id":"2110.12274","title":"\"One-Shot\" Reduction of Additive Artifacts in Medical Images","created":"2021-10-23","cited_by_count":3,"area":null},{"id":"2112.00729","title":"Total-Body Low-Dose CT Image Denoising using Prior Knowledge Transfer Technique with Contrastive Regularization Mechanism","created":"2021-12-01","cited_by_count":3,"area":null},{"id":"2202.00986","title":"Posterior temperature optimized Bayesian models for inverse problems in medical imaging","created":"2022-02-02","cited_by_count":3,"area":null},{"id":"2203.14794","title":"Limited Parameter Denoising for Low-dose X-ray Computed Tomography Using Deep Reinforcement Learning","created":"2022-03-28","cited_by_count":3,"area":null},{"id":"2203.15434","title":"Clean Implicit 3D Structure from Noisy 2D STEM Images","created":"2022-03-29","cited_by_count":3,"area":null},{"id":"2204.03703","title":"Physics-assisted Generative Adversarial Network for X-Ray Tomography","created":"2022-04-07","cited_by_count":3,"area":null},{"id":"2207.07828","title":"Structural Prior Guided Generative Adversarial Transformers for Low-Light Image Enhancement","created":"2022-07-16","cited_by_count":3,"area":null},{"id":"2209.15136","title":"Low-Dose CT Using Denoising Diffusion Probabilistic Model for 20$\\times$ Speedup","created":"2022-09-29","cited_by_count":3,"area":"diffusion"},{"id":"2211.01670","title":"Active CT Reconstruction with a Learned Sampling Policy","created":"2022-11-03","cited_by_count":3,"area":null},{"id":"2303.02110","title":"Need for Objective Task-based Evaluation of Deep Learning-Based Denoising Methods: A Study in the Context of Myocardial Perfusion SPECT","created":"2023-03-03","cited_by_count":3,"area":null},{"id":"2402.01186","title":"Ambient-Pix2PixGAN for Translating Medical Images from Noisy Data","created":"2024-02-02","cited_by_count":3,"area":null},{"id":"2411.10831","title":"Neighboring Slice Noise2Noise: Self-Supervised Medical Image Denoising from Single Noisy Image Volume","created":"2024-11-16","cited_by_count":3,"area":null},{"id":"2506.02149","title":"Tomographic Foundation Model -- FORCE: Flow-Oriented Reconstruction Conditioning Engine","created":"2025-06-02","cited_by_count":3,"area":null},{"id":"2507.06140","title":"LangMamba: A Language-driven Mamba Framework for Low-dose CT Denoising with Vision-language Models","created":"2025-07-08","cited_by_count":3,"area":"mllm"},{"id":"2101.07612","title":"Comparative Evaluation of 3D and 2D Deep Learning Techniques for Semantic Segmentation in CT Scans","created":"2021-01-19","cited_by_count":2,"area":null},{"id":"2108.13458","title":"The Application of Convolutional Neural Networks for Tomographic Reconstruction of Hyperspectral Images","created":"2021-08-30","cited_by_count":2,"area":null},{"id":"2111.06890","title":"Impact of loss functions on the performance of a deep neural network designed to restore low-dose digital mammography","created":"2021-11-12","cited_by_count":2,"area":null},{"id":"2207.02377","title":"Patch-wise Deep Metric Learning for Unsupervised Low-Dose CT Denoising","created":"2022-07-06","cited_by_count":2,"area":null},{"id":"2308.13002","title":"Head-Neck Dual-energy CT Contrast Media Reduction Using Diffusion Models","created":"2023-08-24","cited_by_count":2,"area":"diffusion"},{"id":"2310.03118","title":"Blind CT Image Quality Assessment Using DDPM-derived Content and Transformer-based Evaluator","created":"2023-10-04","cited_by_count":2,"area":null},{"id":"2402.10010","title":"Enhancing signal detectability in learning-based CT reconstruction with a model observer inspired loss function","created":"2024-02-15","cited_by_count":2,"area":null},{"id":"2403.16640","title":"Multi-Scale Texture Loss for CT denoising with GANs","created":"2024-03-25","cited_by_count":2,"area":null},{"id":"2404.09533","title":"WiTUnet: A U-Shaped Architecture Integrating CNN and Transformer for Improved Feature Alignment and Local Information Fusion","created":"2024-04-15","cited_by_count":2,"area":null},{"id":"2407.05259","title":"Multi-scale Conditional Generative Modeling for Microscopic Image Restoration","created":"2024-07-07","cited_by_count":2,"area":"diffusion"},{"id":"2411.00830","title":"Unsupervised Training of a Dynamic Context-Aware Deep Denoising Framework for Low-Dose Fluoroscopic Imaging","created":"2024-10-29","cited_by_count":2,"area":null},{"id":"2504.07927","title":"Zero-Shot Low-dose CT Denoising via Sinogram Flicking","created":"2025-04-10","cited_by_count":2,"area":null},{"id":"2508.20414","title":"Federated Learning for Large Models in Medical Imaging: A Comprehensive Review","created":"2025-08-28","cited_by_count":2,"area":null},{"id":"2102.04590","title":"UVTomo-GAN: An adversarial learning based approach for unknown view X-ray tomographic reconstruction","created":"2021-02-09","cited_by_count":1,"area":null},{"id":"2201.10294","title":"S2MS: Self-Supervised Learning Driven Multi-Spectral CT Image Enhancement","created":"2022-01-25","cited_by_count":1,"area":null},{"id":"2205.00463","title":"A Dataset-free Deep learning Method for Low-Dose CT Image Reconstruction","created":"2022-05-01","cited_by_count":1,"area":null},{"id":"2205.15170","title":"GAN-based Medical Image Small Region Forgery Detection via a Two-Stage Cascade Framework","created":"2022-05-30","cited_by_count":1,"area":null},{"id":"2206.07542","title":"A Deep Generative Model of Neonatal Cortical Surface Development","created":"2022-06-15","cited_by_count":1,"area":null},{"id":"2211.01159","title":"Unsupervised denoising for sparse multi-spectral computed tomography","created":"2022-11-02","cited_by_count":1,"area":null},{"id":"2212.07431","title":"Simulator-Based Self-Supervision for Learned 3D Tomography Reconstruction","created":"2022-12-14","cited_by_count":1,"area":null},{"id":"2301.13358","title":"Hierarchical Disentangled Representation for Invertible Image Denoising and Beyond","created":"2023-01-31","cited_by_count":1,"area":null}],"next_cursor":"100"}