{"total":97,"rows":[{"id":"2209.04747","title":"Diffusion Models in Vision: A Survey","created":"2022-09-10","cited_by_count":1015,"area":"diffusion"},{"id":"2211.07804","title":"Diffusion Models for Medical Image Analysis: A Comprehensive Survey","created":"2022-11-14","cited_by_count":273,"area":"diffusion"},{"id":"2207.08208","title":"Unsupervised Medical Image Translation with Adversarial Diffusion Models","created":"2022-07-17","cited_by_count":192,"area":"diffusion"},{"id":"2309.13415","title":"Dream the Impossible: Outlier Imagination with Diffusion Models","created":"2023-09-23","cited_by_count":77,"area":"diffusion"},{"id":"2402.05210","title":"Anatomically-Controllable Medical Image Generation with Segmentation-Guided Diffusion Models","created":"2024-02-07","cited_by_count":69,"area":"diffusion"},{"id":"2207.12268","title":"What is Healthy? Generative Counterfactual Diffusion for Lesion Localization","created":"2022-07-25","cited_by_count":52,"area":null},{"id":"2303.03758","title":"Patched Diffusion Models for Unsupervised Anomaly Detection in Brain MRI","created":"2023-03-07","cited_by_count":45,"area":"diffusion"},{"id":"2305.13128","title":"GSURE-Based Diffusion Model Training with Corrupted Data","created":"2023-05-22","cited_by_count":40,"area":"diffusion"},{"id":"2307.00754","title":"ImDiffusion: Imputed Diffusion Models for Multivariate Time Series Anomaly Detection","created":"2023-07-03","cited_by_count":40,"area":"diffusion"},{"id":"2312.09608","title":"Faster Diffusion: Rethinking the Role of the Encoder for Diffusion Model Inference","created":"2023-12-15","cited_by_count":34,"area":"diffusion"},{"id":"2309.01111","title":"ArSDM: Colonoscopy Images Synthesis with Adaptive Refinement Semantic Diffusion Models","created":"2023-09-03","cited_by_count":31,"area":"diffusion"},{"id":"2305.19867","title":"Unsupervised Anomaly Detection in Medical Images Using Masked Diffusion Model","created":"2023-05-31","cited_by_count":25,"area":"diffusion"},{"id":"2303.00609","title":"Unsupervised Pathology Detection: A Deep Dive Into the State of the Art","created":"2023-03-01","cited_by_count":24,"area":null},{"id":"2301.08330","title":"The role of noise in denoising models for anomaly detection in medical images","created":"2023-01-19","cited_by_count":23,"area":"diffusion"},{"id":"2303.06410","title":"Brain Diffuser: An End-to-End Brain Image to Brain Network Pipeline","created":"2023-03-11","cited_by_count":21,"area":null},{"id":"2306.03424","title":"GCD-DDPM: A Generative Change Detection Model Based on Difference-Feature Guided DDPM","created":"2023-06-06","cited_by_count":21,"area":"diffusion"},{"id":"2306.01322","title":"Privacy Distillation: Reducing Re-identification Risk of Multimodal Diffusion Models","created":"2023-06-02","cited_by_count":18,"area":"diffusion"},{"id":"2312.04215","title":"Guided Reconstruction with Conditioned Diffusion Models for Unsupervised Anomaly Detection in Brain MRIs","created":"2023-12-07","cited_by_count":18,"area":"diffusion"},{"id":"2307.09547","title":"DreaMR: Diffusion-driven Counterfactual Explanation for Functional MRI","created":"2023-07-18","cited_by_count":14,"area":null},{"id":"2307.08059","title":"LafitE: Latent Diffusion Model with Feature Editing for Unsupervised Multi-class Anomaly Detection","created":"2023-07-16","cited_by_count":13,"area":"diffusion"},{"id":"2306.15733","title":"Face Morphing Attack Detection with Denoising Diffusion Probabilistic Models","created":"2023-06-27","cited_by_count":12,"area":"diffusion"},{"id":"2307.00899","title":"Many tasks make light work: Learning to localise medical anomalies from multiple synthetic tasks","created":"2023-07-03","cited_by_count":12,"area":null},{"id":"2308.16150","title":"Modality Cycles with Masked Conditional Diffusion for Unsupervised Anomaly Segmentation in MRI","created":"2023-08-30","cited_by_count":12,"area":"diffusion"},{"id":"2407.06635","title":"Ensembled Cold-Diffusion Restorations for Unsupervised Anomaly Detection","created":"2024-07-09","cited_by_count":12,"area":null},{"id":"2403.11340","title":"StainDiffuser: MultiTask Dual Diffusion Model for Virtual Staining","created":"2024-03-17","cited_by_count":11,"area":null},{"id":"2502.16872","title":"Mitigating Hallucinations in Diffusion Models through Adaptive Attention Modulation","created":"2025-02-24","cited_by_count":11,"area":"diffusion"},{"id":"2401.09325","title":"Siamese Meets Diffusion Network: SMDNet for Enhanced Change Detection in High-Resolution RS Imagery","created":"2024-01-17","cited_by_count":10,"area":"diffusion"},{"id":"2401.16363","title":"Evaluation of pseudo-healthy image reconstruction for anomaly detection with deep generative models: Application to brain FDG PET","created":"2024-01-29","cited_by_count":10,"area":null},{"id":"2407.12474","title":"Leveraging the Mahalanobis Distance to enhance Unsupervised Brain MRI Anomaly Detection","created":"2024-07-17","cited_by_count":10,"area":null},{"id":"2307.07534","title":"Masked Autoencoders for Unsupervised Anomaly Detection in Medical Images","created":"2023-07-14","cited_by_count":9,"area":null},{"id":"2311.11383","title":"A Survey of Emerging Applications of Diffusion Probabilistic Models in MRI","created":"2023-11-19","cited_by_count":9,"area":"diffusion"},{"id":"2406.02422","title":"IterMask2: Iterative Unsupervised Anomaly Segmentation via Spatial and Frequency Masking for Brain Lesions in MRI","created":"2024-06-04","cited_by_count":9,"area":null},{"id":"2303.17908","title":"Trade-offs in Fine-tuned Diffusion Models Between Accuracy and Interpretability","created":"2023-03-31","cited_by_count":8,"area":"diffusion"},{"id":"2306.03878","title":"Conditional Diffusion Models for Weakly Supervised Medical Image Segmentation","created":"2023-06-06","cited_by_count":8,"area":"diffusion"},{"id":"2405.18511","title":"Feasibility and benefits of joint learning from MRI databases with different brain diseases and modalities for segmentation","created":"2024-05-28","cited_by_count":8,"area":null},{"id":"2506.09368","title":"Anomaly Detection and Generation with Diffusion Models: A Survey","created":"2025-06-11","cited_by_count":8,"area":"diffusion"},{"id":"2302.06670","title":"Unveiling the Unseen: A Comprehensive Survey on Explainable Anomaly Detection in Images and Videos","created":"2023-02-13","cited_by_count":7,"area":null},{"id":"2403.11667","title":"Binary Noise for Binary Tasks: Masked Bernoulli Diffusion for Unsupervised Anomaly Detection","created":"2024-03-18","cited_by_count":7,"area":"diffusion"},{"id":"2404.12920","title":"Zero-Shot Medical Phrase Grounding with Off-the-shelf Diffusion Models","created":"2024-04-19","cited_by_count":7,"area":"diffusion"},{"id":"2504.09549","title":"SD-ReID: View-aware Stable Diffusion for Aerial-Ground Person Re-Identification","created":"2025-04-13","cited_by_count":7,"area":null},{"id":"2506.10233","title":"Conditional diffusion models for guided anomaly detection in brain images using fluid-driven anomaly randomization","created":"2025-06-11","cited_by_count":6,"area":"diffusion"},{"id":"2308.16355","title":"A Recycling Training Strategy for Medical Image Segmentation with Diffusion Denoising Models","created":"2023-08-30","cited_by_count":5,"area":"diffusion"},{"id":"2404.17900","title":"Unsupervised Anomaly Detection via Masked Diffusion Posterior Sampling","created":"2024-04-27","cited_by_count":5,"area":"diffusion"},{"id":"2502.06552","title":"Diffusion Models for Computational Neuroimaging: A Survey","created":"2025-02-10","cited_by_count":5,"area":"diffusion"},{"id":"2210.05952","title":"3D Brain and Heart Volume Generative Models: A Survey","created":"2022-10-12","cited_by_count":4,"area":null},{"id":"2305.00067","title":"Unsupervised Discovery of 3D Hierarchical Structure with Generative Diffusion Features","created":"2023-04-28","cited_by_count":4,"area":"diffusion"},{"id":"2308.03354","title":"Energy-Guided Diffusion Model for CBCT-to-CT Synthesis","created":"2023-08-07","cited_by_count":4,"area":"diffusion"},{"id":"2311.07421","title":"Robust semi-supervised segmentation with timestep ensembling diffusion models","created":"2023-11-13","cited_by_count":4,"area":"diffusion"},{"id":"2312.01904","title":"Unsupervised Anomaly Detection using Aggregated Normative Diffusion","created":"2023-12-04","cited_by_count":4,"area":"diffusion"},{"id":"2410.18866","title":"The Cat and Mouse Game: The Ongoing Arms Race Between Diffusion Models and Detection Methods","created":"2024-10-24","cited_by_count":4,"area":"diffusion"},{"id":"2412.17586","title":"Enhancing Reconstruction-Based Out-of-Distribution Detection in Brain MRI with Model and Metric Ensembles","created":"2024-12-23","cited_by_count":4,"area":null},{"id":"2504.04918","title":"Constitution or Collapse? Exploring Constitutional AI with Llama 3-8B","created":"2025-04-07","cited_by_count":4,"area":null},{"id":"2311.03074","title":"A Two-Stage Generative Model with CycleGAN and Joint Diffusion for MRI-based Brain Tumor Detection","created":"2023-11-06","cited_by_count":3,"area":null},{"id":"2311.09355","title":"Privacy Threats in Stable Diffusion Models","created":"2023-11-15","cited_by_count":3,"area":"diffusion"},{"id":"2312.04382","title":"Adversarial Denoising Diffusion Model for Unsupervised Anomaly Detection","created":"2023-12-07","cited_by_count":3,"area":"diffusion"},{"id":"2410.23834","title":"Denoising Diffusion Models for Anomaly Localization in Medical Images","created":"2024-10-31","cited_by_count":3,"area":"diffusion"},{"id":"2507.12201","title":"RODS: Robust Optimization Inspired Diffusion Sampling for Detecting and Reducing Hallucination in Generative Models","created":"2025-07-16","cited_by_count":3,"area":"diffusion"},{"id":"2309.11125","title":"PSDiff: Diffusion Model for Person Search with Iterative and Collaborative Refinement","created":"2023-09-20","cited_by_count":2,"area":"diffusion"},{"id":"2310.08654","title":"Histogram- and Diffusion-Based Medical Out-of-Distribution Detection","created":"2023-10-12","cited_by_count":2,"area":"diffusion"},{"id":"2404.15683","title":"AnoFPDM: Anomaly Segmentation with Forward Process of Diffusion Models for Brain MRI","created":"2024-04-24","cited_by_count":2,"area":"diffusion"},{"id":"2409.00726","title":"LPUWF-LDM: Enhanced Latent Diffusion Model for Precise Late-phase UWF-FA Generation on Limited Dataset","created":"2024-09-01","cited_by_count":2,"area":null},{"id":"2505.22805","title":"Anomalies by Synthesis: Anomaly Detection using Generative Diffusion Models for Off-Road Navigation","created":"2025-05-28","cited_by_count":2,"area":"diffusion"},{"id":"2602.15315","title":"Training-Free Zero-Shot Anomaly Detection in 3D Brain MRI with 2D Foundation Models","created":"2026-02-17","cited_by_count":2,"area":null},{"id":"2311.09642","title":"Weakly Supervised Anomaly Detection for Chest X-Ray Image","created":"2023-11-16","cited_by_count":1,"area":null},{"id":"2402.11789","title":"Statistical Test for Diffusion-Based Anomaly Localization via Selective Inference","created":"2024-02-19","cited_by_count":1,"area":null},{"id":"2405.04974","title":"Discrepancy-based Diffusion Models for Lesion Detection in Brain MRI","created":"2024-05-08","cited_by_count":1,"area":"diffusion"},{"id":"2406.02653","title":"Pancreatic Tumor Segmentation as Anomaly Detection in CT Images Using Denoising Diffusion Models","created":"2024-06-04","cited_by_count":1,"area":"diffusion"},{"id":"2407.14191","title":"Normative Diffusion Autoencoders: Application to Amyotrophic Lateral Sclerosis","created":"2024-07-19","cited_by_count":1,"area":null},{"id":"2408.00891","title":"Temporal Evolution of Knee Osteoarthritis: A Diffusion-based Morphing Model for X-ray Medical Image Synthesis","created":"2024-08-01","cited_by_count":1,"area":null},{"id":"2408.15958","title":"Efficient Slice Anomaly Detection Network for 3D Brain MRI Volume","created":"2024-08-28","cited_by_count":1,"area":null},{"id":"2506.22504","title":"Patch2Loc: Learning to Localize Patches for Unsupervised Brain Lesion Detection","created":"2025-06-25","cited_by_count":1,"area":null},{"id":"2507.17486","title":"Unsupervised anomaly detection using Bayesian flow networks: application to brain FDG PET in the context of Alzheimer's disease","created":"2025-07-23","cited_by_count":1,"area":null},{"id":"2507.21164","title":"OCSVM-Guided Representation Learning for Unsupervised Anomaly Detection","created":"2025-07-25","cited_by_count":1,"area":null},{"id":"2510.14462","title":"Unsupervised Deep Generative Models for Anomaly Detection in Neuroimaging: A Systematic Scoping Review","created":"2025-10-16","cited_by_count":1,"area":null},{"id":"2307.14701","title":"MIM-OOD: Generative Masked Image Modelling for Out-of-Distribution Detection in Medical Images","created":"2023-07-27","cited_by_count":0,"area":null},{"id":"2310.18091","title":"Adversarial Anomaly Detection using Gaussian Priors and Nonlinear Anomaly Scores","created":"2023-10-27","cited_by_count":0,"area":null},{"id":"2407.00148","title":"Localizing Anomalies via Multiscale Score Matching Analysis","created":"2024-06-28","cited_by_count":0,"area":null},{"id":"2407.04022","title":"Learning Non-Linear Invariants for Unsupervised Out-of-Distribution Detection","created":"2024-07-04","cited_by_count":0,"area":null},{"id":"2410.19535","title":"Detection of Emerging Infectious Diseases in Lung CT based on Spatial Anomaly Patterns","created":"2024-10-25","cited_by_count":0,"area":null},{"id":"2412.05580","title":"Self-Supervised Masked Mesh Learning for Unsupervised Anomaly Detection on 3D Cortical Surfaces","created":"2024-12-07","cited_by_count":0,"area":null},{"id":"2502.08321","title":"Screener: Self-supervised Pathology Segmentation in Medical CT Images","created":"2025-02-12","cited_by_count":0,"area":null},{"id":"2503.09828","title":"Resolution Invariant Autoencoder","created":"2025-03-12","cited_by_count":0,"area":null},{"id":"2506.18544","title":"Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection","created":"2025-06-23","cited_by_count":0,"area":null},{"id":"2506.23460","title":"Contrastive Learning with Diffusion Features for Weakly Supervised Medical Image Segmentation","created":"2025-06-30","cited_by_count":0,"area":"diffusion"},{"id":"2507.08574","title":"Knowledge-Guided Brain Tumor Segmentation via Synchronized Visual-Semantic-Topological Prior Fusion","created":"2025-07-11","cited_by_count":0,"area":null},{"id":"2508.03594","title":"CADD: Context aware disease deviations via restoration of brain images using normative conditional diffusion models","created":"2025-08-05","cited_by_count":0,"area":"diffusion"},{"id":"2510.13684","title":"Generating healthy counterfactuals with denoising diffusion bridge models","created":"2025-10-15","cited_by_count":0,"area":"diffusion"},{"id":"2511.08509","title":"Fast Multi-Organ Fine Segmentation in CT Images with Hierarchical Sparse Sampling and Residual Transformer","created":"2025-11-11","cited_by_count":0,"area":null},{"id":"2602.11703","title":"Semantically Conditioned Diffusion Models for Cerebral DSA Synthesis","created":"2026-02-12","cited_by_count":0,"area":"diffusion"},{"id":"2603.04795","title":"LAW & ORDER: Adaptive Spatial Weighting for Medical Diffusion and Segmentation","created":"2026-03-05","cited_by_count":0,"area":null},{"id":"2605.05891","title":"MTL-MAD: Multi-Task Learners are Effective Medical Anomaly Detectors","created":"2026-05-07","cited_by_count":0,"area":"moe"},{"id":"2605.31193","title":"Geometry-based Schr\\\"odinger Bridges for Trustworthy Multimodal Fusion","created":"2026-05-29","cited_by_count":0,"area":null},{"id":"2606.18749","title":"Toward Training-Free Zero-Shot Anomaly Detection in 3D Medical Images: A Batch-Based Approach Using 2D Foundation Models","created":"2026-06-17","cited_by_count":0,"area":null},{"id":"2607.24703","title":"Panda: Unsupervised Pelvic Anomaly Detection for Real-Time MR Imaging","created":"2026-07-27","cited_by_count":0,"area":null},{"id":"2608.00444","title":"Reconstruction-Shift Discrimination via Mask-Guided Latent Diffusion for Medical Anomaly Detection","created":"2026-08-01","cited_by_count":0,"area":"diffusion"},{"id":"2608.17521","title":"BrainNorm: A Foundation Model that knows Normal via Semantic Atlas Pretraining","created":"2026-08-18","cited_by_count":0,"area":null},{"id":"2610.09670","title":"Quasi-Binarized Autoencoders: An Architecture-Independent Information Bottleneck for Medical Image Anomaly Detection","created":"2026-10-07","cited_by_count":0,"area":null}],"next_cursor":null}