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Deep Learning for Advanced X-ray Detection and Imaging Applications (Record no. 66476)

MARC details
000 -LEADER
fixed length control field 04149nam a22005415i 4500
001 - CONTROL NUMBER
control field 978-3-031-75653-5
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20251030114928.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr nn 008mamaa
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 250122s2024 sz | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783031756535
-- 978-3-031-75653-5
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-3-031-75653-5
Source of number or code doi
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number TK5101-5105.9
072 #7 - SUBJECT CATEGORY CODE
Subject category code TJF
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code TEC024000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code TJF
Source thema
245 10 - TITLE STATEMENT
Title Deep Learning for Advanced X-ray Detection and Imaging Applications
Medium [electronic resource] /
Statement of responsibility, etc. edited by Krzysztof (Kris) Iniewski, Liang (Kevin) Cai.
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2024.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Cham :
Name of producer, publisher, distributor, manufacturer Springer Nature Switzerland :
-- Imprint: Springer,
Date of production, publication, distribution, manufacture, or copyright notice 2024.
300 ## - PHYSICAL DESCRIPTION
Extent VII, 261 p. 75 illus. in color.
Other physical details online resource.
336 ## - CONTENT TYPE
Content type term text
Content type code txt
Source rdacontent
337 ## - MEDIA TYPE
Media type term computer
Media type code c
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term online resource
Carrier type code cr
Source rdacarrier
347 ## - DIGITAL FILE CHARACTERISTICS
File type text file
Encoding format PDF
Source rda
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Deep Learning Techniques for CT Image Denoising and Resolution Enhancement -- , Physically interpretable deep learning reconstruction for photon counting spectral CT -- , Deep learning methods in dual energy CT imaging -- , Performance Evaluation of Implicit Neural Representations in Diagnostic Fan-Beam CT Imaging -- , Learning-Based Material Decomposition for Spectral X-ray Imaging -- , Learning-Based Material Decomposition for Spectral X-ray Imaging -- , Correcting Charge Sharing Distortions in Photon Counting Detectors Utilizing a Spatial-Temporal CNN -- , Machine Learning Approaches for CdZnTe / CdTe Radiation Detectors -- , Enhanced 3D X-ray Tomography: Deep Learning-based Advanced Algorithms for Fiber Instance Segmentation -- , Machine Learning-Based Image Processing in Radiotherapy -- , Deep learning-based image reconstruction of coded-aperture imaging in nuclear security applications -- , Artificial Intelligence for X-ray Photon Counting Technology: Current Status and Future Perspectives.
520 ## - SUMMARY, ETC.
Summary, etc. 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 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element
9 (RLIN) 65750
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element
9 (RLIN) 65751
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element
9 (RLIN) 66607
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element
9 (RLIN) 65752
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element
9 (RLIN) 65753
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element
9 (RLIN) 67319
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Iniewski, Krzysztof (Kris).
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
9 (RLIN) 66514
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Cai, Liang (Kevin).
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
9 (RLIN) 90376
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer Nature eBook
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Printed edition:
International Standard Book Number 9783031756528
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Printed edition:
International Standard Book Number 9783031756542
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Printed edition:
International Standard Book Number 9783031756559
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1007/978-3-031-75653-5">https://doi.org/10.1007/978-3-031-75653-5</a>
912 ## -
-- ZDB-2-SME
912 ## -
-- ZDB-2-SXM

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