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README.md
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- traces
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Multi-modal models are data hungry. While datasets with natural images are abundant, medical image datasets can not afford the same luxury.
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To enable representation learning for medical images at scale, we turn to YouTube, a platform with a large reservoir of open-source medical pedagogical videos.
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We curate MedicalNarratives, a dataset 4.7M medical image-text pairs, with 1M samples containing dense annotations in the form of traces and bounding boxes.
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Similar to \textit{think-aloud} studies where instructors speak while hovering their mouse cursor movements over relevant image regions, 1M images in MedicalNarratives contains localized mouse traces in image pixels, creating a spatial association between the text and pixels.
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Please Note: this version contain some bad images we have since removed and would reupload soon.
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https://medical-narratives.github.io/static/images/ct_examples.png
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