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Synthesizing medical images is now easy to do with deep learning and good datasets, but what is it good for? I've viewed this with a lot of skepticism, but have now started to accumulate some potential use cases, specifically for synthetic #PET in #PETMR
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Maybe I'll start with what I think it is probably NOT good for - diagnosis!
Fundamentally, the information content in synthetic medical images is derived from the distribution and patterns in the data that the model was trained on.
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Fundamentally, the information content in synthetic medical images is derived from the distribution and patterns in the data that the model was trained on.
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For an individual patient, this means that any synthetic images created will just contain the information already in their individual (non-synthetic) images combined with population-level distributions and patterns from the training data.
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