Anatomy-Structured Hierarchical MIL for Weakly-Supervised Thoracic Disease Detection in Chest X-rays

arXiv:2609.33520 · cs.CV · Submitted 2026-09-27 · Read on arXiv

cs.CV

Submitted: 2026-09-27

Updated: 2026-09-27

Comments: Accepted at MICCAI 2026

Code: https://github.com/leotam/MIMIC-CXR-annotations

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Aggregation — 10× in this paper · explained in 1 episode
• Transformer — 6× in this paper · explained in 2 episodes
• Ablation — 4× in this paper · explained in 1 episode
• AGN — 3× in this paper · explained in 1 episode
• Branch-Level Aggregation — 3× in this paper
• Benchmark — 2× in this paper · explained in 2 episodes
• Embeddings — 2× in this paper · explained in 2 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Query-Level Aggregation — 2× in this paper
• Accuracy — 1× in this paper · explained in 1 episode
• Fidelity — 1× in this paper · explained in 2 episodes
• Pseudo-labeling — 1× in this paper · explained in 3 episodes
• Transformer Architecture — 1× in this paper · explained in 2 episodes

Sources

• RadGraph: Extracting Clinical Entities and Relations from Radiology Reports
• DINOv2: Learning Robust Visual Features without Supervision
• CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning
• Accurate Fine-Grained Segmentation of Human Anatomy in Radiographs via Volumetric Pseudo-Labeling
• Chest ImaGenome Dataset for Clinical Reasoning

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