AuntMinnie Digital X-Ray Insider covers the latest AI advancements and challenges in x-ray imaging.
Key Details
- 1South Korean researchers developed a deep learning model estimating pediatric bone mineral density from chest x-rays.
- 2A Radiology study finds radiologists struggle to distinguish AI-generated (deepfake) x-rays from authentic ones.
- 3Finnish research links aortic calcification on chest x-rays to poorer survival post-minor amputation.
- 4Ethiopian researchers use AI to diagnose TB from photographed film chest x-rays in low-resource settings.
- 5UK study shows AI flagging of suspicious x-rays did not reduce diagnosis time for lung cancer.
- 6AI and radiologists both fail to reliably detect interstitial lung abnormalities on standard chest x-rays.
Why It Matters
These studies reflect the growing sophistication and ongoing limitations of AI applications in x-ray imaging, impacting areas from pediatric bone health to disease detection in resource-poor settings. Understanding where AI succeeds and fails helps guide clinical integration and future research.

Source
AuntMinnie
Related News

•Radiology Business
AI Workflow Enables General Radiologists to Match Breast Specialists in Screening
AI-powered workflow helps generalist radiologists detect breast cancer at rates comparable to specialists.

•AuntMinnie
Radiologists Struggle to Spot AI-Generated Radiology Images
Radiologists correctly identify AI-generated images 75% of the time, with CT and MRI images being particularly challenging to spot.

•AuntMinnie
Radiology Leads FDA AI Device Approvals Over Three Decades
Radiology accounts for 76% of all FDA-cleared AI/ML-enabled medical devices as of the end of 2025.