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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 71–78 of 78 papers

TitleStatusHype
Medical Image Generation using Generative Adversarial Networks—0
SkrGAN: Sketching-rendering Unconditional Generative Adversarial Networks for Medical Image Synthesis—0
ADN: Artifact Disentanglement Network for Unsupervised Metal Artifact ReductionCode0
PnP-AdaNet: Plug-and-Play Adversarial Domain Adaptation Network with a Benchmark at Cross-modality Cardiac SegmentationCode0
Medical Image Synthesis for Data Augmentation and Anonymization using Generative Adversarial Networks—0
Generative Adversarial Networks for Image-to-Image Translation on Multi-Contrast MR Images - A Comparison of CycleGAN and UNITCode0
Synthetic Medical Images from Dual Generative Adversarial NetworksCode0
Towards Adversarial Retinal Image SynthesisCode0
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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