ChEX: Interactive Localization and Region Description in Chest X-rays
arxiv(2024)
摘要
Report generation models offer fine-grained textual interpretations of
medical images like chest X-rays, yet they often lack interactivity (i.e. the
ability to steer the generation process through user queries) and localized
interpretability (i.e. visually grounding their predictions), which we deem
essential for future adoption in clinical practice. While there have been
efforts to tackle these issues, they are either limited in their interactivity
by not supporting textual queries or fail to also offer localized
interpretability. Therefore, we propose a novel multitask architecture and
training paradigm integrating textual prompts and bounding boxes for diverse
aspects like anatomical regions and pathologies. We call this approach the
Chest X-Ray Explainer (ChEX). Evaluations across a heterogeneous set of 9 chest
X-ray tasks, including localized image interpretation and report generation,
showcase its competitiveness with SOTA models while additional analysis
demonstrates ChEX's interactive capabilities.
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