FleXray: Universal Clinical X-ray Segmentation
cs.CV, cs.AI
Submitted: 2026-09-22
Updated: 2026-09-23
Comments: 35 pages, 12 figures, 10 tables. Code, models, data, and a browser-based demo at https://flexray.csail.mit.edu
Code: https://github.com/JJGO/thunderpack
Project page: https://aasce19.github.io
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Accurate Fine-Grained Segmentation of Human Anatomy in Radiographs via Volumetric Pseudo-Labeling
- AnyCXR: Human Anatomy Segmentation of Chest X-ray at Any Acquisition Position using Multi-stage Domain Randomized Synthetic Data with Imperfect Annotations and Conditional Joint Annotation Regularization Learning
- Scaling Generative Foundation Models for Chest Radiography with Rectified Flow Transformers
- MURA: Large Dataset for Abnormality Detection in Musculoskeletal Radiographs
- GAN-based Data Augmentation for Chest X-ray Classification
- RoentGen: Vision-Language Foundation Model for Chest X-ray Generation
- Decoupled Weight Decay Regularization
- RAM-W600: A Multi-Task Wrist Dataset and Benchmark for Rheumatoid Arthritis
- VinDr-RibCXR: A Benchmark Dataset for Automatic Segmentation and Labeling of Individual Ribs on Chest X-rays
- Better Aggregation in Test-Time Augmentation
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