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Knowledge-enhanced Visual-Language Pretraining for Computational Pathology
April 16, 2024, 4:48 a.m. | Xiao Zhou, Xiaoman Zhang, Chaoyi Wu, Ya Zhang, Weidi Xie, Yanfeng Wang
cs.CV updates on arXiv.org arxiv.org
Abstract: In this paper, we consider the problem of visual representation learning for computational pathology, by exploiting large-scale image-text pairs gathered from public resources, along with the domain specific knowledge in pathology. Specifically, we make the following contributions: (i) We curate a pathology knowledge tree that consists of 50,470 informative attributes for 4,718 diseases requiring pathology diagnosis from 32 human tissues. To our knowledge, this is the first comprehensive structured pathology knowledge base; (ii) We develop …
abstract arxiv computational cs.cv domain image knowledge language paper pathology pretraining public representation representation learning resources scale text tree type visual
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