zzdyyy/Patho-GAN

Patho-GAN: interpretation + medical data augmentation. Code for paper work "Explainable Diabetic Retinopathy Detection and Retinal Image Generation"

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This tool helps medical researchers and ophthalmologists understand how AI models diagnose diabetic retinopathy and create realistic synthetic retinal images. It takes an existing retinal fundus image as input and can extract specific disease evidence, showing how the AI makes its prediction. It can also generate new, high-quality fundus images with full control over the location and number of lesions, which is useful for augmenting limited medical datasets.

No commits in the last 6 months.

Use this if you need to interpret the diagnostic decisions of an AI model for diabetic retinopathy or generate synthetic retinal images to expand your training data.

Not ideal if you are looking for a ready-to-use clinical diagnostic tool for patients rather than a research framework for model interpretation and data generation.

ophthalmology medical-imaging diabetic-retinopathy AI-explainability medical-data-augmentation
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 9 / 25
Maturity 8 / 25
Community 19 / 25

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Language

Python

License

Last pushed

Apr 20, 2022

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