Med-Banana: Learning Quality-Controlled Medical Image
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Med-Banana: Learning Quality-Controlled Medical Image Editing from Success-and-Failure Trajectories
arXiv:2511.00801v4 Announce Type: replace Abstract: Text-guided medical image editing must satisfy the requested pathology while preserving anatomy, modality-specific appearance, and clinical plausibility. However, existing datasets largely supervise editors with final accepted edits and discard the failed attempts produced during generation.