RadThinking releases a large longitudinal CT VQA dataset stratified into foundation perception questions, single-rule reasoning questions, and compositional multi-step chains grounded in clinical reporting standards for cancer screening.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Medical image parsing is proposed as the central output for the field instead of masks, with an audit showing that none of eleven representative systems produces a well-formed parse containing attributes, relationships, and closure.
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RadThinking: A Dataset for Longitudinal Clinical Reasoning in Radiology
RadThinking releases a large longitudinal CT VQA dataset stratified into foundation perception questions, single-rule reasoning questions, and compositional multi-step chains grounded in clinical reporting standards for cancer screening.
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Beyond Masks: The Case for Medical Image Parsing
Medical image parsing is proposed as the central output for the field instead of masks, with an audit showing that none of eleven representative systems produces a well-formed parse containing attributes, relationships, and closure.