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ACM Multimedia Grand Challenge on ENT Endoscopy Analysis

ACM Multimedia Grand Challenge on ENT Endoscopy Analysis

来源:Arxiv_logoArxiv
英文摘要

Automated analysis of endoscopic imagery is a critical yet underdeveloped component of ENT (ear, nose, and throat) care, hindered by variability in devices and operators, subtle and localized findings, and fine-grained distinctions such as laterality and vocal-fold state. In addition to classification, clinicians require reliable retrieval of similar cases, both visually and through concise textual descriptions. These capabilities are rarely supported by existing public benchmarks. To this end, we introduce ENTRep, the ACM Multimedia 2025 Grand Challenge on ENT endoscopy analysis, which integrates fine-grained anatomical classification with image-to-image and text-to-image retrieval under bilingual (Vietnamese and English) clinical supervision. Specifically, the dataset comprises expert-annotated images, labeled for anatomical region and normal or abnormal status, and accompanied by dual-language narrative descriptions. In addition, we define three benchmark tasks, standardize the submission protocol, and evaluate performance on public and private test splits using server-side scoring. Moreover, we report results from the top-performing teams and provide an insight discussion.

Trong-Thuan Nguyen、Viet-Tham Huynh、Thao Thi Phuong Dao、Ha Nguyen Thi、Tien To Vu Thuy、Uyen Hanh Tran、Tam V. Nguyen、Thanh Dinh Le、Minh-Triet Tran

耳鼻咽喉科学医学研究方法

Trong-Thuan Nguyen,Viet-Tham Huynh,Thao Thi Phuong Dao,Ha Nguyen Thi,Tien To Vu Thuy,Uyen Hanh Tran,Tam V. Nguyen,Thanh Dinh Le,Minh-Triet Tran.ACM Multimedia Grand Challenge on ENT Endoscopy Analysis[EB/OL].(2025-08-06)[2025-08-18].https://arxiv.org/abs/2508.04801.点此复制

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