SOURCE-LINKED INTELLIGENCE

CheXtriev: Anatomy-Centered Representation for Case-Based Retrieval of Chest Radiographs

arXiv · AI, language, vision and robotics · article · Aug 28, 2026 · UTC

We present CheXtriev, a graph-based, anatomy-aware framework for chest radiograph retrieval. Unlike prior methods focussed on global features, our method leverages graph transformers to extract informative features from specific anatomical regions. Furthermore, it captures spatial context and the interplay between anatomical location and findings. This contextualization, grounded in evidence-based anatomy, results in a richer anatomy-aware representation and leads to more accurate, effective and efficient retrieval, particularly for less prevalent findings. CheXtriv outperforms state-of-the-ar

Read original source ↗ Open in workspace

recordType

paper

region

Global