# Rheumatoid Arthritis: Automated Scoring of Radiographic Joint Damage

arXiv: https://arxiv.org/abs/2110.08812 · HTML: https://mlsanity.com/paper/2110.08812/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 8 of its 29 references that are in the map.
- First posted on arXiv 17 Oct 2021.

## Builds on (most cited first, 8 of 8)

- [U-Net: Convolutional Networks for Biomedical Image Segmentation](https://mlsanity.com/paper/1505.04597/) (2015)
- [Very Deep Convolutional Networks for Large-Scale Image Recognition](https://mlsanity.com/paper/1409.1556/) (2014)
- [Fully Convolutional Networks for Semantic Segmentation](https://mlsanity.com/paper/1411.4038/) (2014)
- [YOLOv3: An Incremental Improvement](https://mlsanity.com/paper/1804.02767/) (2018)
- [Spatial Transformer Networks](https://mlsanity.com/paper/1506.02025/) (2015)
- [Comparison of Deep Learning Approaches for Multi-Label Chest X-Ray Classification](https://mlsanity.com/paper/1803.02315/) (2018)
- [Deep Forest](https://mlsanity.com/paper/1702.08835/) (2017)
- [Deep Learning for Rheumatoid Arthritis: Joint Detection and Damage Scoring in X-rays](https://mlsanity.com/paper/2104.13915/) (2021)

## Built on by (most cited first, 3 of 3)

- [Deep Learning Models to Automate the Scoring of Hand Radiographs for Rheumatoid Arthritis](https://mlsanity.com/paper/2406.09980/) (2024)
- [Interpretable Rheumatoid Arthritis Scoring via Anatomy-aware Multiple Instance Learning](https://mlsanity.com/paper/2508.06218/) (2025)
- [Automated Radiographic Total Sharp Score (ARTSS) in Rheumatoid Arthritis: A Solution to Reduce Inter-Intra Reader Variation and Enhancing Clinical Practice](https://mlsanity.com/paper/2509.06854/) (2025)

## Abstract (arXiv)

Rheumatoid arthritis is an autoimmune disease that causes joint damage due to inflammation in the soft tissue lining the joints known as the synovium. It is vital to identify joint damage as soon as possible to provide necessary treatment early and prevent further damage to the bone structures. Radiographs are often used to assess the extent of the joint damage. Currently, the scoring of joint damage from the radiograph takes expertise, effort, and time. Joint damage associated with rheumatoid arthritis is also not quantitated in clinical practice and subjective descriptors are used. In this work, we describe a pipeline of deep learning models to automatically identify and score rheumatoid arthritic joint damage from a radiographic image. Our automatic tool was shown to produce scores with extremely high balanced accuracy within a couple of minutes and utilizing this would remove the subjectivity of the scores between human reviewers.