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New dataset pairs uterine pathology images with reports for AI research

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced TUM-Uteria, a new dataset designed to advance multimodal learning in computational pathology. This dataset pairs whole-slide images of uterine tissue with corresponding diagnostic pathology reports, addressing a critical scarcity of such paired data. TUM-Uteria includes 216 clinical cases with 455 slide-level WSI-report pairs, validated by board-certified pathologists, to support research in AI-assisted diagnosis and automated report generation. AI

IMPACT Enables development of AI tools for more accurate diagnosis and automated reporting in uterine pathology.

RANK_REASON The cluster contains a research paper detailing a new dataset for AI research in computational pathology. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New dataset pairs uterine pathology images with reports for AI research

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The cluster contains a research paper detailing a new dataset for AI research in computational pathology. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Han Li, Jingsong Liu, Ayako Ura, Junlin Hou, Zhengyang Xu, Azar Kazemi, Oskar Thaeter, Christian Grashei, Fabian G\"ulhan, Reza Nasirigerdeh, Xun Ma, Rui Yan, Hao Chen, S. Kevin Zhou, Nassir Navab, Carolin Mogler, Peter Sch\"uffler ·

    Paired Uterine Whole-Slide Images and Pathology Reports for Multimodal Computational Pathology

    arXiv:2607.04020v1 Announce Type: new Abstract: Uterine diseases represent an important category of gynecologic pathology and require accurate histopathological assessment for diagnosis and treatment planning. Whole-slide images (WSI) have enabled the digital transformation of pa…

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