Papers with Code 아카이브

Medical Image Generation

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하위 태스크: 1
평가표: 5
보존된 평가 기록: 10

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>

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/AugustDS/synthetic-medical-benchmark

공식 코드

Overcoming Barriers to Data Sharing with Medical Image Generation: A Comprehensive Evaluation

https://github.com/BradSegal/CXR_PGGAN

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Evaluating the Clinical Realism of Synthetic Chest X-Rays Generated Using Progressively Growing GANs

https://github.com/GabrieleLozupone/LDAE

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Latent Diffusion Autoencoders: Toward Efficient and Meaningful Unsupervised Representation Learning in Medical Imaging

https://github.com/MoPl90/image_translation

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Image Translation for Medical Image Generation -- Ischemic Stroke Lesions

https://github.com/NifTK/NiftyNet

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NiftyNet: a deep-learning platform for medical imaging

https://github.com/Ryann-Ran/Lad

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Devil is in Details: Locality-Aware 3D Abdominal CT Volume Generation for Self-Supervised Organ Segmentation

https://github.com/Tinysqua/UWAT-GAN

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UWAT-GAN: Fundus Fluorescein Angiography Synthesis via Ultra-wide-angle Transformation Multi-scale GAN

https://github.com/YashDeo-York/GenMed

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Metrics that matter: Evaluating image quality metrics for medical image generation

https://github.com/ZKI-PH-ImageAnalysis/GANetic-Loss

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GANetic Loss for Generative Adversarial Networks with a Focus on Medical Applications

https://github.com/alceubissoto/gan-skin-lesion

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Skin Lesion Synthesis with Generative Adversarial Networks

https://github.com/brambozz/medical-diffusion-on-a-budget

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Medical diffusion on a budget: Textual Inversion for medical image generation

https://github.com/bupt-ai-cz/BCI

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BCI: Breast Cancer Immunohistochemical Image Generation through Pyramid Pix2pix

https://github.com/claim-berlin/relict

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RELICT: A Replica Detection Framework for Medical Image Generation

https://github.com/compai-lab/2024-miccai-dgm-daum

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On Differentially Private 3D Medical Image Synthesis with Controllable Latent Diffusion Models

https://github.com/costapt/vess2ret

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Towards Adversarial Retinal Image Synthesis

https://github.com/cyrilzakka/stylegan2-tpu

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MammoGANesis: Controlled Generation of High-Resolution Mammograms for Radiology Education

https://github.com/danny0628/fedcar

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FedCAR: Cross-client Adaptive Re-weighting for Generative Models in Federated Learning

https://github.com/firasgit/medicaldiffusion

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Medical Diffusion: Denoising Diffusion Probabilistic Models for 3D Medical Image Generation

https://github.com/guicamargox/retamd

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Robust deep learning for eye fundus images: Bridging real and synthetic data for enhancing generalization

https://github.com/guicamargox/synthetic-retina-amd

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Robust deep learning for eye fundus images: Bridging real and synthetic data for enhancing generalization

https://github.com/haoningwu3639/MRGen

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MRGen: Diffusion-based Controllable Data Engine for MRI Segmentation towards Unannotated Modalities

https://github.com/hasibzunair/adversarial-lesions

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Melanoma Detection using Adversarial Training and Deep Transfer Learning

https://github.com/ibrahimethemhamamci/generatect

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GenerateCT: Text-Conditional Generation of 3D Chest CT Volumes

https://github.com/jungeun122333/uvi-net

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Data-Efficient Unsupervised Interpolation Without Any Intermediate Frame for 4D Medical Images

https://github.com/liaohaofu/adn

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ADN: Artifact Disentanglement Network for Unsupervised Metal Artifact Reduction

https://github.com/mazurowski-lab/segmentation-guided-diffusion

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Anatomically-Controllable Medical Image Generation with Segmentation-Guided Diffusion Models

https://github.com/mckellwoodland/fid-med-eval

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Feature Extraction for Generative Medical Imaging Evaluation: New Evidence Against an Evolving Trend

https://github.com/mckellwoodland/radfid

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Feature Extraction for Generative Medical Imaging Evaluation: New Evidence Against an Evolving Trend

https://github.com/mhabijan/medical_images_generation

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Generation of Artificial CT Images using Patch-based Conditional Generative Adversarial Networks

https://github.com/nanboy-ronan/backdoor-fedgan

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Backdoor Attack is a Devil in Federated GAN-based Medical Image Synthesis

https://github.com/pfriedri/wdm-3d

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WDM: 3D Wavelet Diffusion Models for High-Resolution Medical Image Synthesis

https://github.com/pooria90/diffecho

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Vision-Language Synthetic Data Enhances Echocardiography Downstream Tasks

https://github.com/raman1121/diffusion_memorization_hpo

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MemControl: Mitigating Memorization in Diffusion Models via Automated Parameter Selection

https://github.com/simontomaskarlsson/GAN-MRI

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Generative Adversarial Networks for Image-to-Image Translation on Multi-Contrast MR Images - A Comparison of CycleGAN and UNIT

https://github.com/simula/Kvasir-VQA

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Kvasir-VQA: A Text-Image Pair GI Tract Dataset

https://github.com/tinysqua/uwafa-gan

공식 코드

UWAFA-GAN: Ultra-Wide-Angle Fluorescein Angiography Transformation via Multi-scale Generation and Registration Enhancement

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