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What Appears Appealing May Not be Significant! -- A Clinical Perspective of Diffusion Models

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arxiv 2407.10029 v1 pith:3S54YJ2P submitted 2024-07-14 cs.CV

classification cs.CV
keywords clinicalappealingdescriptionsdiffusionimagesmodelsrelationvarious
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Various trending image generative techniques, such as diffusion models, have enabled visually appealing outcomes with just text-based descriptions. Unlike general images, where assessing the quality and alignment with text descriptions is trivial, establishing such a relation in a clinical setting proves challenging. This work investigates various strategies to evaluate the clinical significance of synthetic polyp images of different pathologies. We further explore if a relation could be established between qualitative results and their clinical relevance.

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