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Medical Image Generation

Medical image generation is the task of synthesising new medical images.

( Image credit: Towards Adversarial Retinal Image Synthesis )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 51–60 of 78 papers

TitleStatusHype
GANetic Loss for Generative Adversarial Networks with a Focus on Medical ApplicationsCode0
MemControl: Mitigating Memorization in Diffusion Models via Automated Parameter SelectionCode0
UWAFA-GAN: Ultra-Wide-Angle Fluorescein Angiography Transformation via Multi-scale Generation and Registration EnhancementCode0
Safeguarding Medical Image Segmentation Datasets against Unauthorized Training via Contour- and Texture-Aware Perturbations—0
An Ordinal Diffusion Model for Generating Medical Images with Different Severity Levels—0
High-Quality Medical Image Generation from Free-hand Sketch—0
GAN-GA: A Generative Model based on Genetic Algorithm for Medical Image GenerationCode0
BiomedJourney: Counterfactual Biomedical Image Generation by Instruction-Learning from Multimodal Patient Journeys—0
Arbitrary Distributions Mapping via SyMOT-Flow: A Flow-based Approach Integrating Maximum Mean Discrepancy and Optimal Transport—0
Unsupervised Domain Transfer with Conditional Invertible Neural Networks—0
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All datasetsACDCSLIVER07ChestXray14 1024x1024ChestX-ray14Chest X-Ray Images (Pneumonia)

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1StyleGANFID24.74—Unverified
2StyleGAN2 with DiffAugmentFID21.42—Unverified
3StyleGAN2-ADAFID21.17—Unverified
#ModelMetricClaimedVerifiedStatus
1StyleGANFID29.06—Unverified
2StyleGAN2-ADAFID10.78—Unverified
3StyleGAN2 with DiffAugmentFID4.62—Unverified
#ModelMetricClaimedVerifiedStatus
1Progressive Growing GANFID8.02—Unverified
2StyleGAN2-ADAFID3.52—Unverified
#ModelMetricClaimedVerifiedStatus
1StyleGAN2 with DiffAugmentFID3.07—Unverified
#ModelMetricClaimedVerifiedStatus
1DCGANFrechet Inception Distance1.29—Unverified