Applying the ULS23 lesion segmentation model to longitudinal CT data causes a sharp drop in follow-up accuracy and lesion tracking, driven by the model's assumption that every lesion sits at the center of its input patch.
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Unstable Prompts, Unreliable Segmentations: A Challenge for Longitudinal Lesion Analysis
Applying the ULS23 lesion segmentation model to longitudinal CT data causes a sharp drop in follow-up accuracy and lesion tracking, driven by the model's assumption that every lesion sits at the center of its input patch.