Medical Imaging#Chest X-ray Analysis, Medical Image Segmentation, Deep Learning🔬 ResearchAnalyzed: Jan 3, 2026 16:15
MedSAM-based Lung Masking for Chest X-ray Classification
Published:Dec 28, 2025 21:56
•1 min read
•ArXiv
Analysis
This paper addresses the challenge of automated chest X-ray interpretation by leveraging MedSAM for lung region extraction. It explores the impact of lung masking on multi-label abnormality classification, demonstrating that masking strategies should be tailored to the specific task and model architecture. The findings highlight a trade-off between abnormality-specific classification and normal case screening, offering valuable insights for improving the robustness and interpretability of CXR analysis.
Key Takeaways
- •MedSAM is used for lung region extraction in chest X-ray analysis.
- •Lung masking strategies impact classification performance, with trade-offs between abnormality detection and normal case screening.
- •Masking should be tailored to the model architecture and clinical objective.
Reference
“Lung masking should be treated as a controllable spatial prior selected to match the backbone and clinical objective, rather than applied uniformly.”