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Deep learning for advanced X-ray detection and imaging applications

Record Type:	Electronic resources : Monograph/item
Title/Author:	Deep learning for advanced X-ray detection and imaging applications/ edited by Krzysztof (Kris) Iniewski, Liang (Kevin) Cai.
other author:	Iniewski, Krzysztof.
Published:	Cham :Springer Nature Switzerland : : 2024.,
Description:	vii, 261 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Radiography, Medical. -
Online resource:	https://doi.org/10.1007/978-3-031-75653-5
ISBN:	9783031756535

Deep learning for advanced X-ray detection and imaging applications
Deep learning for advanced X-ray detection and imaging applications[electronic resource] /edited by Krzysztof (Kris) Iniewski, Liang (Kevin) Cai. - Cham :Springer Nature Switzerland :2024. - vii, 261 p. :ill., digital ;24 cm.

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.

ISBN: 9783031756535

Standard No.: 10.1007/978-3-031-75653-5doiSubjects--Topical Terms:

826376
Radiography, Medical.

LC Class. No.: RC78

Dewey Class. No.: 616.07572

Deep learning for advanced X-ray detection and imaging applications
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245 0 0 $a Deep learning for advanced X-ray detection and imaging applications $h [electronic resource] / $c edited by Krzysztof (Kris) Iniewski, Liang (Kevin) Cai.
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300 $a vii, 261 p. : $b ill., digital ; $c 24 cm.
520 $a 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.
650 0 $a Radiography, Medical. $3 826376
650 0 $a Artificial intelligence $x Medical applications. $3 900591
650 1 4 $a Microwaves, RF Engineering and Optical Communications. $3 3538694
650 2 4 $a Photonics and Optical Engineering. $3 3591865
650 2 4 $a Optics and Photonics. $3 1060604
700 1 $a Iniewski, Krzysztof. $3 1097192
700 1 $a Cai, Liang. $3 3603972
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