TL;DR
This paper introduces RAM-W600, a comprehensive multi-task wrist dataset with annotations for RA diagnosis, including instance segmentation and bone erosion scoring, to advance computer-aided diagnosis research.
Contribution
It provides the first public dataset for wrist bone instance segmentation and BE scoring, supporting diverse RA-related research tasks.
Findings
Dataset includes 1048 wrist radiographs from 388 patients.
Annotations cover 618 images for segmentation and 800 for BE scores.
Dataset aims to facilitate RA diagnosis and progression research.
Abstract
Rheumatoid arthritis (RA) is a common autoimmune disease that has been the focus of research in computer-aided diagnosis (CAD) and disease monitoring. In clinical settings, conventional radiography (CR) is widely used for the screening and evaluation of RA due to its low cost and accessibility. The wrist is a critical region for the diagnosis of RA. However, CAD research in this area remains limited, primarily due to the challenges in acquiring high-quality instance-level annotations. (i) The wrist comprises numerous small bones with narrow joint spaces, complex structures, and frequent overlaps, requiring detailed anatomical knowledge for accurate annotation. (ii) Disease progression in RA often leads to osteophyte, bone erosion (BE), and even bony ankylosis, which alter bone morphology and increase annotation difficulty, necessitating expertise in rheumatology. This work presents a…
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