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arXiv Machine Learning By Songxiao Yang, Haolin Wang, Yao Fu, Junmu Peng, Lin Fan, Hongruixuan Chen, Jian Song, Masayuki Ikebe, Shinya Takamaeda-Yamazaki, Masatoshi Okutomi, Tamotsu Kamishima, Yafei Ou

RAM-H1200: A Unified Evaluation and Dataset on Hand Radiographs for Rheumatoid Arthritis

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RAM‑H1200 is a new public benchmark comprising 1,200 hand radiographs from six medical centers, each annotated with whole‑hand bone instance segmentation, pixel‑level bone erosion masks, joint regions of interest, and joint‑level Sharp‑van der Heijde (SvdH) scores for bone erosion and joint space narrowing. The dataset enables unified multi‑level analysis of anatomical structure, localized erosive pathology, and clinically standardized RA severity, filling a gap in existing resources that lack full‑hand coverage and fine‑grained annotations. Initial benchmark results show strong performance in bone segmentation but highlight that bone erosion segmentation remains a significant challenge, underscoring the dataset’s potential to advance quantitative RA analysis.

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