biomedia-mira/causal-gen

(ICML 2023) High Fidelity Image Counterfactuals with Probabilistic Causal Models

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Emerging

This project helps medical professionals and researchers understand how changes to underlying health factors might alter medical images, like X-rays or MRI scans. You input an existing medical image and specify a hypothetical change to a condition, and it outputs a new image showing what that change might look like. This is useful for scientists exploring disease progression or clinicians planning interventions, allowing them to visualize 'what-if' scenarios.

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Use this if you need to generate high-fidelity counterfactual medical images to explore the impact of specific causal factors on visual medical data.

Not ideal if you are looking to diagnose conditions directly from images or require real-time image generation for clinical decision-making.

medical-imaging causal-inference radiology biomedical-research disease-modeling
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 8 / 25
Maturity 16 / 25
Community 14 / 25

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Stars

67

Forks

10

Language

Python

License

MIT

Last pushed

Mar 24, 2025

Commits (30d)

0

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