
A new AI algorithm can reconstruct 3D images from only 2-4 X-rays, reducing radiation exposure by up to 99%.
Key Details
- 1AI tool generates 3D reconstructions using just 2-4 X-ray images.
- 2Patient radiation exposure reduced by 95-99% compared to standard CT scans.
- 3Algorithm achieves 97% accuracy benchmark versus conventional CT imaging.
- 4Developed by researchers at Hong Kong University of Science and Technology (HKUST).
- 5Already used to assist surgeons in preoperative planning, with future goals including 3D implant creation and enhanced imaging precision.
Why It Matters
Such a drastic reduction in radiation exposure and imaging costs could transform how 3D imaging is used for surgical planning. High-accuracy reconstructions from minimal x-ray data open new possibilities for safer, more accessible radiology workflows.

Source
Health Imaging
Related News

•Radiology Business
Hybrid AI Approach Cuts Mammography Workload by 38%
A Dutch research team demonstrated that a 'hybrid' AI strategy can reduce radiologist workload in mammography screening by nearly 40% without affecting performance.

•AuntMinnie
Habitat AI Model Improves Risk Stratification of Lung Nodules on LDCT
A 'habitat' AI model outperforms standard 2D approaches in stratifying lung adenocarcinoma risk in subsolid nodules on low-dose CT scans.

•AuntMinnie
AI Model Uses Chest CT to Diagnose and Grade COPD Severity
A machine learning model based on chest CT images accurately diagnoses and grades the severity of COPD.