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Medical Image Generation
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Medical image generation is the task of synthesising new medical images.
<span style="color:grey; opacity: 0.6">( Image credit: Towards Adversarial Retinal Image Synthesis )</span>
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Med-Art: Diffusion Transformer for 2D Medical Text-to-Image Generation
Metrics that matter: Evaluating image quality metrics for medical image generation
Causal Disentanglement for Robust Long-tail Medical Image Generation
seg2med: a bridge from artificial anatomy to multimodal medical images
Latent Diffusion Autoencoders: Toward Efficient and Meaningful Unsupervised Representation Learning in Medical Imaging
Language-Guided Trajectory Traversal in Disentangled Stable Diffusion Latent Space for Factorized Medical Image Generation
Towards Interpretable Counterfactual Generation via Multimodal Autoregression
RL4Med-DDPO: Reinforcement Learning for Controlled Guidance Towards Diverse Medical Image Generation using Vision-Language Foundation Models
RELICT: A Replica Detection Framework for Medical Image Generation
Diffusion-Based Approaches in Medical Image Generation and Analysis
3D MedDiffusion: A 3D Medical Diffusion Model for Controllable and High-quality Medical Image Generation
FedCAR: Cross-client Adaptive Re-weighting for Generative Models in Federated Learning
MRGen: Diffusion-based Controllable Data Engine for MRI Segmentation towards Unannotated Modalities
IMPROVE: Improving Medical Plausibility without Reliance on HumanValidation -- An Enhanced Prototype-Guided Diffusion Framework
Mediffusion: Joint Diffusion for Self-Explainable Semi-Supervised Classification and Medical Image Generation
Exploring Variational Autoencoders for Medical Image Generation: A Comprehensive Study
Conditional Diffusion Model for Longitudinal Medical Image Generation
Clinical Evaluation of Medical Image Synthesis: A Case Study in Wireless Capsule Endoscopy
Evaluating Utility of Memory Efficient Medical Image Generation: A Study on Lung Nodule Segmentation
RadGazeGen: Radiomics and Gaze-guided Medical Image Generation using Diffusion Models
Devil is in Details: Locality-Aware 3D Abdominal CT Volume Generation for Self-Supervised Organ Segmentation
Introducing SDICE: An Index for Assessing Diversity of Synthetic Medical Datasets
Kvasir-VQA: A Text-Image Pair GI Tract Dataset
MedDiT: A Knowledge-Controlled Diffusion Transformer Framework for Dynamic Medical Image Generation in Virtual Simulated Patient
On Differentially Private 3D Medical Image Synthesis with Controllable Latent Diffusion Models
Enhancing Label-efficient Medical Image Segmentation with Text-guided Diffusion Models
Soft Masked Mamba Diffusion Model for CT to MRI Conversion
Rapid Review of Generative AI in Smart Medical Applications
GANetic Loss for Generative Adversarial Networks with a Focus on Medical Applications
MemControl: Mitigating Memorization in Diffusion Models via Automated Parameter Selection
UWAFA-GAN: Ultra-Wide-Angle Fluorescein Angiography Transformation via Multi-scale Generation and Registration Enhancement
Data-Efficient Unsupervised Interpolation Without Any Intermediate Frame for 4D Medical Images
Vision-Language Synthetic Data Enhances Echocardiography Downstream Tasks
Safeguarding Medical Image Segmentation Datasets against Unauthorized Training via Contour- and Texture-Aware Perturbations
An Ordinal Diffusion Model for Generating Medical Images with Different Severity Levels
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