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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

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Showing 21–30 of 78 papers

TitleStatusHype
RadGazeGen: Radiomics and Gaze-guided Medical Image Generation using Diffusion Models—0
Devil is in Details: Locality-Aware 3D Abdominal CT Volume Generation for Self-Supervised Organ SegmentationCode0
Introducing SDICE: An Index for Assessing Diversity of Synthetic Medical Datasets—0
Kvasir-VQA: A Text-Image Pair GI Tract DatasetCode0
MedDiT: A Knowledge-Controlled Diffusion Transformer Framework for Dynamic Medical Image Generation in Virtual Simulated Patient—0
On Differentially Private 3D Medical Image Synthesis with Controllable Latent Diffusion ModelsCode0
Enhancing Label-efficient Medical Image Segmentation with Text-guided Diffusion Models—0
Soft Masked Mamba Diffusion Model for CT to MRI ConversionCode2
Rapid Review of Generative AI in Smart Medical Applications—0
GANetic Loss for Generative Adversarial Networks with a Focus on Medical ApplicationsCode0
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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