Advanced Machine Vision Paradigms for Medical Image Analysis

Computer vision and machine intelligence paradigms are prominent in the domain of medical image applications, including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics. Medical image analysis and understanding are daunting tasks owing to the massive influx of multi-modal medical image data generated during routine clinal practice. Advanced computer vision and machine intelligence approaches have been employed in recent years in the field of image processing and computer vision. However, due to the unstructured nature of medical imaging data and the volume of data produced during routine clinical processes, the applicability of these meta-heuristic algorithms remains to be investigated. Advanced Machine Vision Paradigms for Medical Image Analysis presents an overview of how medical imaging data can be analyzed to provide better diagnosis and treatment of disease. Computer vision techniques can explore texture, shape, contour and prior knowledge along with contextual information, from image sequence and 3D/4D information which helps with better human understanding. Many powerful tools have been developed through image segmentation, machine learning, pattern classification, tracking, and reconstruction to surface much needed quantitative information not easily available through the analysis of trained human specialists. The aim of the book is for medical imaging professionals to acquire and interpret the data, and for computer vision professionals to learn how to provide enhanced medical information by using computer vision techniques. The ultimate objective is to benefit patients without adding to already high healthcare costs. Explores major emerging trends in technology which are supporting the current advancement of medical image analysis with the help of computational intelligence Highlights the advancement of conventional approaches in the field of medical image processing Investigates novel techniques and reviews the state-of-the-art in the areas of machine learning, computer vision, soft computing techniques, as well as their applications in medical image analysis Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Gandhi, Tapan K. [verfasserIn] Bhattacharyya, Siddhartha [mitwirkender] De, Sourav [mitwirkender] Konar, Debanjan [mitwirkender] Dey, Sandip [mitwirkender]

Format:	E-Book
Sprache:	Englisch

Erschienen:	San Diego: Elsevier Science & Technology ; 2020 ©2020

Schlagwörter:	Computer vision Diagnostic imaging, Data processing Diagnostic imaging ; Data processing Vision par ordinateur Imagerie pour le diagnostic - Informatique

Anmerkung:	Description based on publisher supplied metadata and other sources
Umfang:	1 online resource (310 pages)

Reihe:	Hybrid Computational Intelligence for Pattern Analysis and Understanding Ser. Hybrid Computational Intelligence for Pattern Analysis and Understanding Series

Links:	Link aufrufen Link aufrufen
ISBN:	978-0-12-819295-5

Katalog-ID:	1728615887

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allfields	9780128192955 978-0-12-819295-5 (DE-627)1728615887 (DE-599)KXP1728615887 (OCoLC)1196250404 (ELSEVIER)on1184057206 (EBP)05865058X DE-627 ger DE-627 rda eng RC78.7.D53 616.07/54028537 Gandhi, Tapan K. verfasserin aut Advanced Machine Vision Paradigms for Medical Image Analysis San Diego Elsevier Science & Technology 2020 ©2020 1 online resource (310 pages) Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Hybrid Computational Intelligence for Pattern Analysis and Understanding Ser. Hybrid Computational Intelligence for Pattern Analysis and Understanding Series Description based on publisher supplied metadata and other sources Computer vision and machine intelligence paradigms are prominent in the domain of medical image applications, including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics. Medical image analysis and understanding are daunting tasks owing to the massive influx of multi-modal medical image data generated during routine clinal practice. Advanced computer vision and machine intelligence approaches have been employed in recent years in the field of image processing and computer vision. However, due to the unstructured nature of medical imaging data and the volume of data produced during routine clinical processes, the applicability of these meta-heuristic algorithms remains to be investigated. Advanced Machine Vision Paradigms for Medical Image Analysis presents an overview of how medical imaging data can be analyzed to provide better diagnosis and treatment of disease. Computer vision techniques can explore texture, shape, contour and prior knowledge along with contextual information, from image sequence and 3D/4D information which helps with better human understanding. Many powerful tools have been developed through image segmentation, machine learning, pattern classification, tracking, and reconstruction to surface much needed quantitative information not easily available through the analysis of trained human specialists. The aim of the book is for medical imaging professionals to acquire and interpret the data, and for computer vision professionals to learn how to provide enhanced medical information by using computer vision techniques. The ultimate objective is to benefit patients without adding to already high healthcare costs. Explores major emerging trends in technology which are supporting the current advancement of medical image analysis with the help of computational intelligence Highlights the advancement of conventional approaches in the field of medical image processing Investigates novel techniques and reviews the state-of-the-art in the areas of machine learning, computer vision, soft computing techniques, as well as their applications in medical image analysis Computer vision Diagnostic imaging Data processing Computer vision Diagnostic imaging ; Data processing Vision par ordinateur (CaQQLa)201-0074889 Imagerie pour le diagnostic - Informatique (CaQQLa)201-0146124 Bhattacharyya, Siddhartha mitwirkender ctb De, Sourav mitwirkender ctb Konar, Debanjan mitwirkender ctb Dey, Sandip mitwirkender ctb 012819295X 9780128192955 012819295X 9780128192955 Erscheint auch als Druck-Ausgabe 012819295X 9780128192955 https://www.sciencedirect.com/science/book/9780128192955 X:ELSEVIER Verlag lizenzpflichtig GBV-33-Freedom 2022 BSZ-33-EBS-HSAA GBV-33-EBS-MRI GBV-33-EBS-ZHB GBV-33-Freedom 2021 ZDB-33-EBS ZDB-33-EGE 2020 ZDB-33-ESD GBV-33-Freedom 2023 BSZ-33-ESD-L1FH GBV-33-EBS-HST BSZ-33-EBS-C1UB GBV_ILN_60 ISIL_DE-705 SYSFLAG_1 GBV_KXP GBV_ILN_105 ISIL_DE-841 GBV_ILN_132 ISIL_DE-959 GBV_ILN_185 ISIL_DE-Sra5 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2020 ISIL_DE-Ch1 GBV_ILN_2057 ISIL_DE-L189 GBV_ILN_2111 ISIL_DE-944 BO 045F 616.07/54028537 60 01 0705 4236040123 00 --%%-- --%%-- s --%%-- Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. Nur für Angehörige der HSU: Volltextzugang von außerhalb des Campus mit Anmeldung über Shibboleth mit Ihrer Bibliothekskennung z 20-12-22 105 01 0841 4074485796 OLR-ELV-TEST Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Die Weitergabe an Dritte sowie systematisches Downloaden sind untersagt. Testzugang ZHB Lübeck z 26-02-22 132 01 0959 4500005110 EBS Elsevier Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. Zeitlich begrenzte Lizenzierung k 13-03-24 185 01 3519 4514755737 OLR-EBS Vervielfältigungen (z.B. 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Zugriff von außerhalb nur für HCU-Angehörige möglich https://www.sciencedirect.com/science/book/9780128192955 2020 01 DE-Ch1 https://www.sciencedirect.com/science/book/9780128192955 2057 01 DE-L189 HTWK-Zugang https://www.sciencedirect.com/science/book/9780128192955 2111 01 DE-944 https://www.sciencedirect.com/science/book/9780128192955 132 01 0959 00 EBooks Elsevier Engineering 105 01 0841 OLR-ELV-TEST 132 01 0959 EBS Elsevier 185 01 3519 OLR-EBS 370 01 4370 EBS Elsevier
spelling	9780128192955 978-0-12-819295-5 (DE-627)1728615887 (DE-599)KXP1728615887 (OCoLC)1196250404 (ELSEVIER)on1184057206 (EBP)05865058X DE-627 ger DE-627 rda eng RC78.7.D53 616.07/54028537 Gandhi, Tapan K. verfasserin aut Advanced Machine Vision Paradigms for Medical Image Analysis San Diego Elsevier Science & Technology 2020 ©2020 1 online resource (310 pages) Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Hybrid Computational Intelligence for Pattern Analysis and Understanding Ser. Hybrid Computational Intelligence for Pattern Analysis and Understanding Series Description based on publisher supplied metadata and other sources Computer vision and machine intelligence paradigms are prominent in the domain of medical image applications, including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics. Medical image analysis and understanding are daunting tasks owing to the massive influx of multi-modal medical image data generated during routine clinal practice. Advanced computer vision and machine intelligence approaches have been employed in recent years in the field of image processing and computer vision. However, due to the unstructured nature of medical imaging data and the volume of data produced during routine clinical processes, the applicability of these meta-heuristic algorithms remains to be investigated. Advanced Machine Vision Paradigms for Medical Image Analysis presents an overview of how medical imaging data can be analyzed to provide better diagnosis and treatment of disease. Computer vision techniques can explore texture, shape, contour and prior knowledge along with contextual information, from image sequence and 3D/4D information which helps with better human understanding. Many powerful tools have been developed through image segmentation, machine learning, pattern classification, tracking, and reconstruction to surface much needed quantitative information not easily available through the analysis of trained human specialists. The aim of the book is for medical imaging professionals to acquire and interpret the data, and for computer vision professionals to learn how to provide enhanced medical information by using computer vision techniques. The ultimate objective is to benefit patients without adding to already high healthcare costs. Explores major emerging trends in technology which are supporting the current advancement of medical image analysis with the help of computational intelligence Highlights the advancement of conventional approaches in the field of medical image processing Investigates novel techniques and reviews the state-of-the-art in the areas of machine learning, computer vision, soft computing techniques, as well as their applications in medical image analysis Computer vision Diagnostic imaging Data processing Computer vision Diagnostic imaging ; Data processing Vision par ordinateur (CaQQLa)201-0074889 Imagerie pour le diagnostic - Informatique (CaQQLa)201-0146124 Bhattacharyya, Siddhartha mitwirkender ctb De, Sourav mitwirkender ctb Konar, Debanjan mitwirkender ctb Dey, Sandip mitwirkender ctb 012819295X 9780128192955 012819295X 9780128192955 Erscheint auch als Druck-Ausgabe 012819295X 9780128192955 https://www.sciencedirect.com/science/book/9780128192955 X:ELSEVIER Verlag lizenzpflichtig GBV-33-Freedom 2022 BSZ-33-EBS-HSAA GBV-33-EBS-MRI GBV-33-EBS-ZHB GBV-33-Freedom 2021 ZDB-33-EBS ZDB-33-EGE 2020 ZDB-33-ESD GBV-33-Freedom 2023 BSZ-33-ESD-L1FH GBV-33-EBS-HST BSZ-33-EBS-C1UB GBV_ILN_60 ISIL_DE-705 SYSFLAG_1 GBV_KXP GBV_ILN_105 ISIL_DE-841 GBV_ILN_132 ISIL_DE-959 GBV_ILN_185 ISIL_DE-Sra5 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2020 ISIL_DE-Ch1 GBV_ILN_2057 ISIL_DE-L189 GBV_ILN_2111 ISIL_DE-944 BO 045F 616.07/54028537 60 01 0705 4236040123 00 --%%-- --%%-- s --%%-- Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. Nur für Angehörige der HSU: Volltextzugang von außerhalb des Campus mit Anmeldung über Shibboleth mit Ihrer Bibliothekskennung z 20-12-22 105 01 0841 4074485796 OLR-ELV-TEST Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Die Weitergabe an Dritte sowie systematisches Downloaden sind untersagt. Testzugang ZHB Lübeck z 26-02-22 132 01 0959 4500005110 EBS Elsevier Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. Zeitlich begrenzte Lizenzierung k 13-03-24 185 01 3519 4514755737 OLR-EBS Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Die Weitergabe an Dritte sowie systematisches Downloaden sind untersagt. z 23-04-24 370 01 4370 4540282611 EBS Elsevier Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. i z 20-06-24 2020 01 DE-Ch1 4520348528 00 --%%-- --%%-- n n Campuslizenz l01 03-05-24 2057 01 DE-L189 4467503145 00 --%%-- --%%-- --%%-- n Campuslizenz l01 24-01-24 2111 01 DE-944 4046024151 00 --%%-- E-Book Elsevier --%%-- n Elektronischer Volltext - Campuslizenz l01 27-01-22 60 01 0705 https://www.sciencedirect.com/science/book/9780128192955 105 01 0841 https://www.sciencedirect.com/science/book/9780128192955 132 01 0959 Zugriff nur für Angehörige der Hochschule Osnabrück im Hochschulnetz https://www.sciencedirect.com/science/book/9780128192955 185 01 3519 https://www.sciencedirect.com/science/book/9780128192955 370 01 4370 E-Book: Zugriff im HCU-Netz. Zugriff von außerhalb nur für HCU-Angehörige möglich https://www.sciencedirect.com/science/book/9780128192955 2020 01 DE-Ch1 https://www.sciencedirect.com/science/book/9780128192955 2057 01 DE-L189 HTWK-Zugang https://www.sciencedirect.com/science/book/9780128192955 2111 01 DE-944 https://www.sciencedirect.com/science/book/9780128192955 132 01 0959 00 EBooks Elsevier Engineering 105 01 0841 OLR-ELV-TEST 132 01 0959 EBS Elsevier 185 01 3519 OLR-EBS 370 01 4370 EBS Elsevier
allfields_unstemmed	9780128192955 978-0-12-819295-5 (DE-627)1728615887 (DE-599)KXP1728615887 (OCoLC)1196250404 (ELSEVIER)on1184057206 (EBP)05865058X DE-627 ger DE-627 rda eng RC78.7.D53 616.07/54028537 Gandhi, Tapan K. verfasserin aut Advanced Machine Vision Paradigms for Medical Image Analysis San Diego Elsevier Science & Technology 2020 ©2020 1 online resource (310 pages) Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Hybrid Computational Intelligence for Pattern Analysis and Understanding Ser. Hybrid Computational Intelligence for Pattern Analysis and Understanding Series Description based on publisher supplied metadata and other sources Computer vision and machine intelligence paradigms are prominent in the domain of medical image applications, including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics. Medical image analysis and understanding are daunting tasks owing to the massive influx of multi-modal medical image data generated during routine clinal practice. Advanced computer vision and machine intelligence approaches have been employed in recent years in the field of image processing and computer vision. However, due to the unstructured nature of medical imaging data and the volume of data produced during routine clinical processes, the applicability of these meta-heuristic algorithms remains to be investigated. Advanced Machine Vision Paradigms for Medical Image Analysis presents an overview of how medical imaging data can be analyzed to provide better diagnosis and treatment of disease. Computer vision techniques can explore texture, shape, contour and prior knowledge along with contextual information, from image sequence and 3D/4D information which helps with better human understanding. Many powerful tools have been developed through image segmentation, machine learning, pattern classification, tracking, and reconstruction to surface much needed quantitative information not easily available through the analysis of trained human specialists. The aim of the book is for medical imaging professionals to acquire and interpret the data, and for computer vision professionals to learn how to provide enhanced medical information by using computer vision techniques. The ultimate objective is to benefit patients without adding to already high healthcare costs. Explores major emerging trends in technology which are supporting the current advancement of medical image analysis with the help of computational intelligence Highlights the advancement of conventional approaches in the field of medical image processing Investigates novel techniques and reviews the state-of-the-art in the areas of machine learning, computer vision, soft computing techniques, as well as their applications in medical image analysis Computer vision Diagnostic imaging Data processing Computer vision Diagnostic imaging ; Data processing Vision par ordinateur (CaQQLa)201-0074889 Imagerie pour le diagnostic - Informatique (CaQQLa)201-0146124 Bhattacharyya, Siddhartha mitwirkender ctb De, Sourav mitwirkender ctb Konar, Debanjan mitwirkender ctb Dey, Sandip mitwirkender ctb 012819295X 9780128192955 012819295X 9780128192955 Erscheint auch als Druck-Ausgabe 012819295X 9780128192955 https://www.sciencedirect.com/science/book/9780128192955 X:ELSEVIER Verlag lizenzpflichtig GBV-33-Freedom 2022 BSZ-33-EBS-HSAA GBV-33-EBS-MRI GBV-33-EBS-ZHB GBV-33-Freedom 2021 ZDB-33-EBS ZDB-33-EGE 2020 ZDB-33-ESD GBV-33-Freedom 2023 BSZ-33-ESD-L1FH GBV-33-EBS-HST BSZ-33-EBS-C1UB GBV_ILN_60 ISIL_DE-705 SYSFLAG_1 GBV_KXP GBV_ILN_105 ISIL_DE-841 GBV_ILN_132 ISIL_DE-959 GBV_ILN_185 ISIL_DE-Sra5 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2020 ISIL_DE-Ch1 GBV_ILN_2057 ISIL_DE-L189 GBV_ILN_2111 ISIL_DE-944 BO 045F 616.07/54028537 60 01 0705 4236040123 00 --%%-- --%%-- s --%%-- Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. Nur für Angehörige der HSU: Volltextzugang von außerhalb des Campus mit Anmeldung über Shibboleth mit Ihrer Bibliothekskennung z 20-12-22 105 01 0841 4074485796 OLR-ELV-TEST Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Die Weitergabe an Dritte sowie systematisches Downloaden sind untersagt. Testzugang ZHB Lübeck z 26-02-22 132 01 0959 4500005110 EBS Elsevier Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. Zeitlich begrenzte Lizenzierung k 13-03-24 185 01 3519 4514755737 OLR-EBS Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Die Weitergabe an Dritte sowie systematisches Downloaden sind untersagt. z 23-04-24 370 01 4370 4540282611 EBS Elsevier Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. i z 20-06-24 2020 01 DE-Ch1 4520348528 00 --%%-- --%%-- n n Campuslizenz l01 03-05-24 2057 01 DE-L189 4467503145 00 --%%-- --%%-- --%%-- n Campuslizenz l01 24-01-24 2111 01 DE-944 4046024151 00 --%%-- E-Book Elsevier --%%-- n Elektronischer Volltext - Campuslizenz l01 27-01-22 60 01 0705 https://www.sciencedirect.com/science/book/9780128192955 105 01 0841 https://www.sciencedirect.com/science/book/9780128192955 132 01 0959 Zugriff nur für Angehörige der Hochschule Osnabrück im Hochschulnetz https://www.sciencedirect.com/science/book/9780128192955 185 01 3519 https://www.sciencedirect.com/science/book/9780128192955 370 01 4370 E-Book: Zugriff im HCU-Netz. Zugriff von außerhalb nur für HCU-Angehörige möglich https://www.sciencedirect.com/science/book/9780128192955 2020 01 DE-Ch1 https://www.sciencedirect.com/science/book/9780128192955 2057 01 DE-L189 HTWK-Zugang https://www.sciencedirect.com/science/book/9780128192955 2111 01 DE-944 https://www.sciencedirect.com/science/book/9780128192955 132 01 0959 00 EBooks Elsevier Engineering 105 01 0841 OLR-ELV-TEST 132 01 0959 EBS Elsevier 185 01 3519 OLR-EBS 370 01 4370 EBS Elsevier
allfieldsGer	9780128192955 978-0-12-819295-5 (DE-627)1728615887 (DE-599)KXP1728615887 (OCoLC)1196250404 (ELSEVIER)on1184057206 (EBP)05865058X DE-627 ger DE-627 rda eng RC78.7.D53 616.07/54028537 Gandhi, Tapan K. verfasserin aut Advanced Machine Vision Paradigms for Medical Image Analysis San Diego Elsevier Science & Technology 2020 ©2020 1 online resource (310 pages) Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Hybrid Computational Intelligence for Pattern Analysis and Understanding Ser. Hybrid Computational Intelligence for Pattern Analysis and Understanding Series Description based on publisher supplied metadata and other sources Computer vision and machine intelligence paradigms are prominent in the domain of medical image applications, including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics. Medical image analysis and understanding are daunting tasks owing to the massive influx of multi-modal medical image data generated during routine clinal practice. Advanced computer vision and machine intelligence approaches have been employed in recent years in the field of image processing and computer vision. However, due to the unstructured nature of medical imaging data and the volume of data produced during routine clinical processes, the applicability of these meta-heuristic algorithms remains to be investigated. Advanced Machine Vision Paradigms for Medical Image Analysis presents an overview of how medical imaging data can be analyzed to provide better diagnosis and treatment of disease. Computer vision techniques can explore texture, shape, contour and prior knowledge along with contextual information, from image sequence and 3D/4D information which helps with better human understanding. Many powerful tools have been developed through image segmentation, machine learning, pattern classification, tracking, and reconstruction to surface much needed quantitative information not easily available through the analysis of trained human specialists. The aim of the book is for medical imaging professionals to acquire and interpret the data, and for computer vision professionals to learn how to provide enhanced medical information by using computer vision techniques. The ultimate objective is to benefit patients without adding to already high healthcare costs. Explores major emerging trends in technology which are supporting the current advancement of medical image analysis with the help of computational intelligence Highlights the advancement of conventional approaches in the field of medical image processing Investigates novel techniques and reviews the state-of-the-art in the areas of machine learning, computer vision, soft computing techniques, as well as their applications in medical image analysis Computer vision Diagnostic imaging Data processing Computer vision Diagnostic imaging ; Data processing Vision par ordinateur (CaQQLa)201-0074889 Imagerie pour le diagnostic - Informatique (CaQQLa)201-0146124 Bhattacharyya, Siddhartha mitwirkender ctb De, Sourav mitwirkender ctb Konar, Debanjan mitwirkender ctb Dey, Sandip mitwirkender ctb 012819295X 9780128192955 012819295X 9780128192955 Erscheint auch als Druck-Ausgabe 012819295X 9780128192955 https://www.sciencedirect.com/science/book/9780128192955 X:ELSEVIER Verlag lizenzpflichtig GBV-33-Freedom 2022 BSZ-33-EBS-HSAA GBV-33-EBS-MRI GBV-33-EBS-ZHB GBV-33-Freedom 2021 ZDB-33-EBS ZDB-33-EGE 2020 ZDB-33-ESD GBV-33-Freedom 2023 BSZ-33-ESD-L1FH GBV-33-EBS-HST BSZ-33-EBS-C1UB GBV_ILN_60 ISIL_DE-705 SYSFLAG_1 GBV_KXP GBV_ILN_105 ISIL_DE-841 GBV_ILN_132 ISIL_DE-959 GBV_ILN_185 ISIL_DE-Sra5 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2020 ISIL_DE-Ch1 GBV_ILN_2057 ISIL_DE-L189 GBV_ILN_2111 ISIL_DE-944 BO 045F 616.07/54028537 60 01 0705 4236040123 00 --%%-- --%%-- s --%%-- Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. Nur für Angehörige der HSU: Volltextzugang von außerhalb des Campus mit Anmeldung über Shibboleth mit Ihrer Bibliothekskennung z 20-12-22 105 01 0841 4074485796 OLR-ELV-TEST Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Die Weitergabe an Dritte sowie systematisches Downloaden sind untersagt. Testzugang ZHB Lübeck z 26-02-22 132 01 0959 4500005110 EBS Elsevier Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. Zeitlich begrenzte Lizenzierung k 13-03-24 185 01 3519 4514755737 OLR-EBS Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Die Weitergabe an Dritte sowie systematisches Downloaden sind untersagt. z 23-04-24 370 01 4370 4540282611 EBS Elsevier Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. i z 20-06-24 2020 01 DE-Ch1 4520348528 00 --%%-- --%%-- n n Campuslizenz l01 03-05-24 2057 01 DE-L189 4467503145 00 --%%-- --%%-- --%%-- n Campuslizenz l01 24-01-24 2111 01 DE-944 4046024151 00 --%%-- E-Book Elsevier --%%-- n Elektronischer Volltext - Campuslizenz l01 27-01-22 60 01 0705 https://www.sciencedirect.com/science/book/9780128192955 105 01 0841 https://www.sciencedirect.com/science/book/9780128192955 132 01 0959 Zugriff nur für Angehörige der Hochschule Osnabrück im Hochschulnetz https://www.sciencedirect.com/science/book/9780128192955 185 01 3519 https://www.sciencedirect.com/science/book/9780128192955 370 01 4370 E-Book: Zugriff im HCU-Netz. Zugriff von außerhalb nur für HCU-Angehörige möglich https://www.sciencedirect.com/science/book/9780128192955 2020 01 DE-Ch1 https://www.sciencedirect.com/science/book/9780128192955 2057 01 DE-L189 HTWK-Zugang https://www.sciencedirect.com/science/book/9780128192955 2111 01 DE-944 https://www.sciencedirect.com/science/book/9780128192955 132 01 0959 00 EBooks Elsevier Engineering 105 01 0841 OLR-ELV-TEST 132 01 0959 EBS Elsevier 185 01 3519 OLR-EBS 370 01 4370 EBS Elsevier
allfieldsSound	9780128192955 978-0-12-819295-5 (DE-627)1728615887 (DE-599)KXP1728615887 (OCoLC)1196250404 (ELSEVIER)on1184057206 (EBP)05865058X DE-627 ger DE-627 rda eng RC78.7.D53 616.07/54028537 Gandhi, Tapan K. verfasserin aut Advanced Machine Vision Paradigms for Medical Image Analysis San Diego Elsevier Science & Technology 2020 ©2020 1 online resource (310 pages) Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Hybrid Computational Intelligence for Pattern Analysis and Understanding Ser. Hybrid Computational Intelligence for Pattern Analysis and Understanding Series Description based on publisher supplied metadata and other sources Computer vision and machine intelligence paradigms are prominent in the domain of medical image applications, including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics. Medical image analysis and understanding are daunting tasks owing to the massive influx of multi-modal medical image data generated during routine clinal practice. Advanced computer vision and machine intelligence approaches have been employed in recent years in the field of image processing and computer vision. However, due to the unstructured nature of medical imaging data and the volume of data produced during routine clinical processes, the applicability of these meta-heuristic algorithms remains to be investigated. Advanced Machine Vision Paradigms for Medical Image Analysis presents an overview of how medical imaging data can be analyzed to provide better diagnosis and treatment of disease. Computer vision techniques can explore texture, shape, contour and prior knowledge along with contextual information, from image sequence and 3D/4D information which helps with better human understanding. Many powerful tools have been developed through image segmentation, machine learning, pattern classification, tracking, and reconstruction to surface much needed quantitative information not easily available through the analysis of trained human specialists. The aim of the book is for medical imaging professionals to acquire and interpret the data, and for computer vision professionals to learn how to provide enhanced medical information by using computer vision techniques. The ultimate objective is to benefit patients without adding to already high healthcare costs. Explores major emerging trends in technology which are supporting the current advancement of medical image analysis with the help of computational intelligence Highlights the advancement of conventional approaches in the field of medical image processing Investigates novel techniques and reviews the state-of-the-art in the areas of machine learning, computer vision, soft computing techniques, as well as their applications in medical image analysis Computer vision Diagnostic imaging Data processing Computer vision Diagnostic imaging ; Data processing Vision par ordinateur (CaQQLa)201-0074889 Imagerie pour le diagnostic - Informatique (CaQQLa)201-0146124 Bhattacharyya, Siddhartha mitwirkender ctb De, Sourav mitwirkender ctb Konar, Debanjan mitwirkender ctb Dey, Sandip mitwirkender ctb 012819295X 9780128192955 012819295X 9780128192955 Erscheint auch als Druck-Ausgabe 012819295X 9780128192955 https://www.sciencedirect.com/science/book/9780128192955 X:ELSEVIER Verlag lizenzpflichtig GBV-33-Freedom 2022 BSZ-33-EBS-HSAA GBV-33-EBS-MRI GBV-33-EBS-ZHB GBV-33-Freedom 2021 ZDB-33-EBS ZDB-33-EGE 2020 ZDB-33-ESD GBV-33-Freedom 2023 BSZ-33-ESD-L1FH GBV-33-EBS-HST BSZ-33-EBS-C1UB GBV_ILN_60 ISIL_DE-705 SYSFLAG_1 GBV_KXP GBV_ILN_105 ISIL_DE-841 GBV_ILN_132 ISIL_DE-959 GBV_ILN_185 ISIL_DE-Sra5 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2020 ISIL_DE-Ch1 GBV_ILN_2057 ISIL_DE-L189 GBV_ILN_2111 ISIL_DE-944 BO 045F 616.07/54028537 60 01 0705 4236040123 00 --%%-- --%%-- s --%%-- Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. Nur für Angehörige der HSU: Volltextzugang von außerhalb des Campus mit Anmeldung über Shibboleth mit Ihrer Bibliothekskennung z 20-12-22 105 01 0841 4074485796 OLR-ELV-TEST Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Die Weitergabe an Dritte sowie systematisches Downloaden sind untersagt. Testzugang ZHB Lübeck z 26-02-22 132 01 0959 4500005110 EBS Elsevier Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. Zeitlich begrenzte Lizenzierung k 13-03-24 185 01 3519 4514755737 OLR-EBS Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Die Weitergabe an Dritte sowie systematisches Downloaden sind untersagt. z 23-04-24 370 01 4370 4540282611 EBS Elsevier Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. i z 20-06-24 2020 01 DE-Ch1 4520348528 00 --%%-- --%%-- n n Campuslizenz l01 03-05-24 2057 01 DE-L189 4467503145 00 --%%-- --%%-- --%%-- n Campuslizenz l01 24-01-24 2111 01 DE-944 4046024151 00 --%%-- E-Book Elsevier --%%-- n Elektronischer Volltext - Campuslizenz l01 27-01-22 60 01 0705 https://www.sciencedirect.com/science/book/9780128192955 105 01 0841 https://www.sciencedirect.com/science/book/9780128192955 132 01 0959 Zugriff nur für Angehörige der Hochschule Osnabrück im Hochschulnetz https://www.sciencedirect.com/science/book/9780128192955 185 01 3519 https://www.sciencedirect.com/science/book/9780128192955 370 01 4370 E-Book: Zugriff im HCU-Netz. Zugriff von außerhalb nur für HCU-Angehörige möglich https://www.sciencedirect.com/science/book/9780128192955 2020 01 DE-Ch1 https://www.sciencedirect.com/science/book/9780128192955 2057 01 DE-L189 HTWK-Zugang https://www.sciencedirect.com/science/book/9780128192955 2111 01 DE-944 https://www.sciencedirect.com/science/book/9780128192955 132 01 0959 00 EBooks Elsevier Engineering 105 01 0841 OLR-ELV-TEST 132 01 0959 EBS Elsevier 185 01 3519 OLR-EBS 370 01 4370 EBS Elsevier
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topic_facet	Computer vision Diagnostic imaging Diagnostic imaging ; Data processing Vision par ordinateur Imagerie pour le diagnostic - Informatique Data processing
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publishDateDaySort_date	2020-01-01T00:00:00Z
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topic_title	RC78.7.D53 616.07/54028537 132 01 0959 00 EBooks Elsevier Engineering Advanced Machine Vision Paradigms for Medical Image Analysis Computer vision Diagnostic imaging Data processing Diagnostic imaging ; Data processing Vision par ordinateur (CaQQLa)201-0074889 Imagerie pour le diagnostic - Informatique (CaQQLa)201-0146124
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title_full	Advanced Machine Vision Paradigms for Medical Image Analysis
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title_sort	advanced machine vision paradigms for medical image analysis
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title_auth	Advanced Machine Vision Paradigms for Medical Image Analysis
abstract	Computer vision and machine intelligence paradigms are prominent in the domain of medical image applications, including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics. Medical image analysis and understanding are daunting tasks owing to the massive influx of multi-modal medical image data generated during routine clinal practice. Advanced computer vision and machine intelligence approaches have been employed in recent years in the field of image processing and computer vision. However, due to the unstructured nature of medical imaging data and the volume of data produced during routine clinical processes, the applicability of these meta-heuristic algorithms remains to be investigated. Advanced Machine Vision Paradigms for Medical Image Analysis presents an overview of how medical imaging data can be analyzed to provide better diagnosis and treatment of disease. Computer vision techniques can explore texture, shape, contour and prior knowledge along with contextual information, from image sequence and 3D/4D information which helps with better human understanding. Many powerful tools have been developed through image segmentation, machine learning, pattern classification, tracking, and reconstruction to surface much needed quantitative information not easily available through the analysis of trained human specialists. The aim of the book is for medical imaging professionals to acquire and interpret the data, and for computer vision professionals to learn how to provide enhanced medical information by using computer vision techniques. The ultimate objective is to benefit patients without adding to already high healthcare costs. Explores major emerging trends in technology which are supporting the current advancement of medical image analysis with the help of computational intelligence Highlights the advancement of conventional approaches in the field of medical image processing Investigates novel techniques and reviews the state-of-the-art in the areas of machine learning, computer vision, soft computing techniques, as well as their applications in medical image analysis Description based on publisher supplied metadata and other sources
abstractGer	Computer vision and machine intelligence paradigms are prominent in the domain of medical image applications, including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics. Medical image analysis and understanding are daunting tasks owing to the massive influx of multi-modal medical image data generated during routine clinal practice. Advanced computer vision and machine intelligence approaches have been employed in recent years in the field of image processing and computer vision. However, due to the unstructured nature of medical imaging data and the volume of data produced during routine clinical processes, the applicability of these meta-heuristic algorithms remains to be investigated. Advanced Machine Vision Paradigms for Medical Image Analysis presents an overview of how medical imaging data can be analyzed to provide better diagnosis and treatment of disease. Computer vision techniques can explore texture, shape, contour and prior knowledge along with contextual information, from image sequence and 3D/4D information which helps with better human understanding. Many powerful tools have been developed through image segmentation, machine learning, pattern classification, tracking, and reconstruction to surface much needed quantitative information not easily available through the analysis of trained human specialists. The aim of the book is for medical imaging professionals to acquire and interpret the data, and for computer vision professionals to learn how to provide enhanced medical information by using computer vision techniques. The ultimate objective is to benefit patients without adding to already high healthcare costs. Explores major emerging trends in technology which are supporting the current advancement of medical image analysis with the help of computational intelligence Highlights the advancement of conventional approaches in the field of medical image processing Investigates novel techniques and reviews the state-of-the-art in the areas of machine learning, computer vision, soft computing techniques, as well as their applications in medical image analysis Description based on publisher supplied metadata and other sources
abstract_unstemmed	Computer vision and machine intelligence paradigms are prominent in the domain of medical image applications, including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics. Medical image analysis and understanding are daunting tasks owing to the massive influx of multi-modal medical image data generated during routine clinal practice. Advanced computer vision and machine intelligence approaches have been employed in recent years in the field of image processing and computer vision. However, due to the unstructured nature of medical imaging data and the volume of data produced during routine clinical processes, the applicability of these meta-heuristic algorithms remains to be investigated. Advanced Machine Vision Paradigms for Medical Image Analysis presents an overview of how medical imaging data can be analyzed to provide better diagnosis and treatment of disease. Computer vision techniques can explore texture, shape, contour and prior knowledge along with contextual information, from image sequence and 3D/4D information which helps with better human understanding. Many powerful tools have been developed through image segmentation, machine learning, pattern classification, tracking, and reconstruction to surface much needed quantitative information not easily available through the analysis of trained human specialists. The aim of the book is for medical imaging professionals to acquire and interpret the data, and for computer vision professionals to learn how to provide enhanced medical information by using computer vision techniques. The ultimate objective is to benefit patients without adding to already high healthcare costs. Explores major emerging trends in technology which are supporting the current advancement of medical image analysis with the help of computational intelligence Highlights the advancement of conventional approaches in the field of medical image processing Investigates novel techniques and reviews the state-of-the-art in the areas of machine learning, computer vision, soft computing techniques, as well as their applications in medical image analysis Description based on publisher supplied metadata and other sources
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title_short	Advanced Machine Vision Paradigms for Medical Image Analysis
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fullrecord_marcxml	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000cam a22002652 4500</leader><controlfield tag="001">1728615887</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20240503140149.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">200902s2020 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9780128192955</subfield><subfield code="9">978-0-12-819295-5</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)1728615887</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)KXP1728615887</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1196250404</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)on1184057206</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(EBP)05865058X</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">RC78.7.D53</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">616.07/54028537</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Gandhi, Tapan K.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Advanced Machine Vision Paradigms for Medical Image Analysis</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">San Diego</subfield><subfield code="b">Elsevier Science & Technology</subfield><subfield code="c">2020</subfield></datafield><datafield tag="264" ind1=" " ind2="4"><subfield code="c">©2020</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 online resource (310 pages)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="0" ind2=" "><subfield code="a">Hybrid Computational Intelligence for Pattern Analysis and Understanding Ser.</subfield></datafield><datafield tag="490" ind1="0" ind2=" "><subfield code="a">Hybrid Computational Intelligence for Pattern Analysis and Understanding Series</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Description based on publisher supplied metadata and other sources</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Computer vision and machine intelligence paradigms are prominent in the domain of medical image applications, including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics. Medical image analysis and understanding are daunting tasks owing to the massive influx of multi-modal medical image data generated during routine clinal practice. Advanced computer vision and machine intelligence approaches have been employed in recent years in the field of image processing and computer vision. However, due to the unstructured nature of medical imaging data and the volume of data produced during routine clinical processes, the applicability of these meta-heuristic algorithms remains to be investigated. Advanced Machine Vision Paradigms for Medical Image Analysis presents an overview of how medical imaging data can be analyzed to provide better diagnosis and treatment of disease. Computer vision techniques can explore texture, shape, contour and prior knowledge along with contextual information, from image sequence and 3D/4D information which helps with better human understanding. Many powerful tools have been developed through image segmentation, machine learning, pattern classification, tracking, and reconstruction to surface much needed quantitative information not easily available through the analysis of trained human specialists. The aim of the book is for medical imaging professionals to acquire and interpret the data, and for computer vision professionals to learn how to provide enhanced medical information by using computer vision techniques. The ultimate objective is to benefit patients without adding to already high healthcare costs. Explores major emerging trends in technology which are supporting the current advancement of medical image analysis with the help of computational intelligence Highlights the advancement of conventional approaches in the field of medical image processing Investigates novel techniques and reviews the state-of-the-art in the areas of machine learning, computer vision, soft computing techniques, as well as their applications in medical image analysis</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Computer vision</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Diagnostic imaging</subfield><subfield code="x">Data processing</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Computer vision</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Diagnostic imaging ; Data processing</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Vision par 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