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How much can we trust our pipelines to give us meaningful answers? One way to answer this is to introduce tiny perturbations throughout our pipelines, and see how much our answers change. This project aims at making it easier to perform these analyses and answer these questions.
Does it only focus on numerical instabilities or on measurement noise as well?
For instance adding random Rician noise to MRI input and evaluate the stability of result.
@bpinsard Both! An important point is understanding the relationship between numerical instabilities which we can simulate using data-agnostic techniques like those above, and those from more structured data-specific noise. Rician, of course, at the top of the list for MRI 😄
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