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Deep Learning for Advanced X-ray Detection and Imaging Applications

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This book provides a comprehensive overview of the latest advances in applying Artificial Intelligence (AI) to advanced X-ray imaging, with a particular focus on its medical applications. Readers will discover why AI is set to revolutionize traditional signal processing and image reconstruction with vastly improved performance. The authors illustrate how Machine Learning (ML) and Deep Learning (DL) significantly advance X-ray detection analysis, image reconstruction, and other crucial steps. This book also reveals how these technologies enable photon counting detector-based X-ray Computed Tomography (CT), which has the potential not only to improve current CT images but also enable new clinical applications, such as providing higher spatial resolution, better soft tissue contrast, K-edge imaging, and simultaneous multi-contrast agent imaging.

  • Explores the latest advances in applying Artificial Intelligence to advanced X-ray imaging;
  • Provides reviews on innovative techniques for signal formation and image reconstruction process;
  • Showcases the application of deep learning algorithms in Photon-Counting CT.

Informations bibliographiques

février 2025, env. 190 Pages, Anglais
Springer International Publishing
978-3-031-75652-8

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