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ct_fm_feature_extractor

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Hi @fepegar ,

While we performed the pre-training on 24x128x128 with 3x1x1 spacing, we experimented with different patch sizes for the feature extractor when it came to search and retrieval. I would prioritize the needs of the use-case - i.e. if you're looking at specific local regions or larger FOVs. The only recommendation I would make is to keep the spacing to 3x1x1 (z,y,x) when possible.

Thank you, @surajpaib ! What would you use for the full FOV?

For the full FOV but whatever you get out of your data post resampling to 3x1x1 should work (followed this approach for the 3D-MIR datasets)

One consideration with full FOV would be that the final features might benefit from not just looking at avg pooled values. I'd suggest concat or such depending on what you might use these features for downstream.

Thank you!