⁠Scientific publication highlights

High quality images at a low radiation dose are required to optimize the early detection of lung cancer while minimizing the downstream risks of repeated radiation exposure to yield the benefits of lung cancer screening. This study explores the use of a silver-based spectral filter (SilverBeam) and an AI reconstruction algorithm (AiCE) to achieve significant dose reduction while preserving image quality and lung nodule detection accuracy across varying dose levels.

Conclusion:

"The Silver filter and DLR (Deep Learning Reconstruction) can significantly improve image quality and nodule detection capability compared with the Copper filter and other reconstruction methods at each of radiation doses used."

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