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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 31–40 of 78 papers

TitleStatusHype
Conditional Diffusion Model for Longitudinal Medical Image Generation—0
Conditional Generation of Medical Images via Disentangled Adversarial Inference—0
Current State of Community-Driven Radiological AI Deployment in Medical Imaging—0
Diffusion-Based Approaches in Medical Image Generation and Analysis—0
Enhancing Label-efficient Medical Image Segmentation with Text-guided Diffusion Models—0
3D MedDiffusion: A 3D Medical Diffusion Model for Controllable and High-quality Medical Image Generation—0
Evaluating Utility of Memory Efficient Medical Image Generation: A Study on Lung Nodule Segmentation—0
Evaluation of Deep Convolutional Generative Adversarial Networks for data augmentation of chest X-ray images—0
Exploring Variational Autoencoders for Medical Image Generation: A Comprehensive Study—0
GANs for Medical Image Synthesis: An Empirical Study—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