Medical image synthesis: methods and clinical applications
Image synthesis across and within medical imaging modalities is an active area of research with broad applications in radiology and radiation oncology. This book covers the principles and methods of medical image synthesis, along with state-of-the-art research.First, various traditional non-learning...
Gespeichert in:
Weitere Verfasser: | |
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Format: | Buch |
Sprache: | English |
Veröffentlicht: |
Boca Raton ; New York ; London
CRC Press
2024
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Ausgabe: | First edition |
Schriftenreihe: | Imaging in medical diagnosis and therapy
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Schlagworte: | |
Zusammenfassung: | Image synthesis across and within medical imaging modalities is an active area of research with broad applications in radiology and radiation oncology. This book covers the principles and methods of medical image synthesis, along with state-of-the-art research.First, various traditional non-learning-based, traditional machine-learning-based, and recent deep-learning-based medical image synthesis methods are reviewed. Second, specific applications of different inter- and intra-modality image synthesis tasks and of synthetic image-aided segmentation and registration are introduced and summarized, listing and highlighting the proposed methods, study designs, and reported performances with the related clinical applications of representative studies. Third, the clinical usages of medical image synthesis, such as treatment planning and image-guided adaptive radiotherapy, are discussed. Last, the limitations and current challenges of various medical synthesis applications are explored, along with future trends and potential solutions to solve these difficulties.The benefits of medical image synthesis have sparked growing interest in a number of advanced clinical applications, such as magnetic resonance imaging (MRI)-only radiation therapy treatment planning and positron emission tomography (PET)/MRI scanning. This book will be a comprehensive and exciting resource for undergraduates, graduates, researchers, and practitioners |
Beschreibung: | Part 1: Methods and Principles 1. Non-Deep-Learning-Based Medical Image Synthesis Methods 2. Deep Learning-Based Medical Image Synthesis Methods Part 2: Applications of Inter-Modality Image Synthesis 3. MRI-Based Image Synthesis 4. CBCT/CT-Based Image Synthesis 5. CT-Based DVF/Ventilation/Perfusion Imaging 6. Image-Based Dose Planning Prediction Part 3: Applications of Intra-Modality Image Synthesis 7. Medical Imaging Denoising 8. Attenuation Correction for Quantitative PET/MR Imaging 9. High-Resolution Medical Image Estimation 10. 2D-3D Transformation for 3D Volumetric Imaging 11. Multi-Modality MRI Synthesis 12. Multi-Energy CT Transformation and Virtual Monoenergetic Imaging 13. Metal Artifact Reduction Part 4: Other Applications of Medical Image Synthesis 14. Synthetic Image-Aided Segmentation 15. Synthetic Image-Aided Registration 16. CT Image Standardization Using Deep Image Synthesis Models Part 5: Clinic Usage of Medical Image Synthesis 17. Image-Guided Adaptive Radiotherapy Part 6: Perspectives 18. Validation and Evaluation Metrics 19. Limitation and Future Trends |
Beschreibung: | x, 307 Seiten Illustrationen 590 gr |
ISBN: | 9781032133881 9781032152844 |
Internformat
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520 | |a Image synthesis across and within medical imaging modalities is an active area of research with broad applications in radiology and radiation oncology. This book covers the principles and methods of medical image synthesis, along with state-of-the-art research.First, various traditional non-learning-based, traditional machine-learning-based, and recent deep-learning-based medical image synthesis methods are reviewed. Second, specific applications of different inter- and intra-modality image synthesis tasks and of synthetic image-aided segmentation and registration are introduced and summarized, listing and highlighting the proposed methods, study designs, and reported performances with the related clinical applications of representative studies. Third, the clinical usages of medical image synthesis, such as treatment planning and image-guided adaptive radiotherapy, are discussed. Last, the limitations and current challenges of various medical synthesis applications are explored, along with future trends and potential solutions to solve these difficulties.The benefits of medical image synthesis have sparked growing interest in a number of advanced clinical applications, such as magnetic resonance imaging (MRI)-only radiation therapy treatment planning and positron emission tomography (PET)/MRI scanning. This book will be a comprehensive and exciting resource for undergraduates, graduates, researchers, and practitioners | ||
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id | DE-604.BV049597233 |
illustrated | Illustrated |
index_date | 2024-07-03T23:34:08Z |
indexdate | 2024-07-20T07:24:51Z |
institution | BVB |
isbn | 9781032133881 9781032152844 |
language | English |
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physical | x, 307 Seiten Illustrationen 590 gr |
publishDate | 2024 |
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publisher | CRC Press |
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series2 | Imaging in medical diagnosis and therapy |
spelling | Medical image synthesis methods and clinical applications edited by Xiaofeng Yang First edition Boca Raton ; New York ; London CRC Press 2024 x, 307 Seiten Illustrationen 590 gr txt rdacontent n rdamedia nc rdacarrier Imaging in medical diagnosis and therapy Part 1: Methods and Principles 1. Non-Deep-Learning-Based Medical Image Synthesis Methods 2. Deep Learning-Based Medical Image Synthesis Methods Part 2: Applications of Inter-Modality Image Synthesis 3. MRI-Based Image Synthesis 4. CBCT/CT-Based Image Synthesis 5. CT-Based DVF/Ventilation/Perfusion Imaging 6. Image-Based Dose Planning Prediction Part 3: Applications of Intra-Modality Image Synthesis 7. Medical Imaging Denoising 8. Attenuation Correction for Quantitative PET/MR Imaging 9. High-Resolution Medical Image Estimation 10. 2D-3D Transformation for 3D Volumetric Imaging 11. Multi-Modality MRI Synthesis 12. Multi-Energy CT Transformation and Virtual Monoenergetic Imaging 13. Metal Artifact Reduction Part 4: Other Applications of Medical Image Synthesis 14. Synthetic Image-Aided Segmentation 15. Synthetic Image-Aided Registration 16. CT Image Standardization Using Deep Image Synthesis Models Part 5: Clinic Usage of Medical Image Synthesis 17. Image-Guided Adaptive Radiotherapy Part 6: Perspectives 18. Validation and Evaluation Metrics 19. Limitation and Future Trends Image synthesis across and within medical imaging modalities is an active area of research with broad applications in radiology and radiation oncology. This book covers the principles and methods of medical image synthesis, along with state-of-the-art research.First, various traditional non-learning-based, traditional machine-learning-based, and recent deep-learning-based medical image synthesis methods are reviewed. Second, specific applications of different inter- and intra-modality image synthesis tasks and of synthetic image-aided segmentation and registration are introduced and summarized, listing and highlighting the proposed methods, study designs, and reported performances with the related clinical applications of representative studies. Third, the clinical usages of medical image synthesis, such as treatment planning and image-guided adaptive radiotherapy, are discussed. Last, the limitations and current challenges of various medical synthesis applications are explored, along with future trends and potential solutions to solve these difficulties.The benefits of medical image synthesis have sparked growing interest in a number of advanced clinical applications, such as magnetic resonance imaging (MRI)-only radiation therapy treatment planning and positron emission tomography (PET)/MRI scanning. This book will be a comprehensive and exciting resource for undergraduates, graduates, researchers, and practitioners bicssc / Biomedical engineering bicssc / Medicine - general issues bicssc / Life sciences - general issues bicssc / Medical physics bicssc / Medical imaging bicssc / Oncology bisacsh / MEDICAL / Oncology / General bisacsh / SCIENCE / Physics / General Bildgebendes Verfahren (DE-588)4006617-4 gnd rswk-swf Bildanalyse (DE-588)4145391-8 gnd rswk-swf Bildgebendes Verfahren (DE-588)4006617-4 s Bildanalyse (DE-588)4145391-8 s DE-604 Yang, Xiaofeng edt Erscheint auch als Online-Ausgabe 978-1-003-24345-8 |
spellingShingle | Medical image synthesis methods and clinical applications bicssc / Biomedical engineering bicssc / Medicine - general issues bicssc / Life sciences - general issues bicssc / Medical physics bicssc / Medical imaging bicssc / Oncology bisacsh / MEDICAL / Oncology / General bisacsh / SCIENCE / Physics / General Bildgebendes Verfahren (DE-588)4006617-4 gnd Bildanalyse (DE-588)4145391-8 gnd |
subject_GND | (DE-588)4006617-4 (DE-588)4145391-8 |
title | Medical image synthesis methods and clinical applications |
title_auth | Medical image synthesis methods and clinical applications |
title_exact_search | Medical image synthesis methods and clinical applications |
title_exact_search_txtP | Medical image synthesis methods and clinical applications |
title_full | Medical image synthesis methods and clinical applications edited by Xiaofeng Yang |
title_fullStr | Medical image synthesis methods and clinical applications edited by Xiaofeng Yang |
title_full_unstemmed | Medical image synthesis methods and clinical applications edited by Xiaofeng Yang |
title_short | Medical image synthesis |
title_sort | medical image synthesis methods and clinical applications |
title_sub | methods and clinical applications |
topic | bicssc / Biomedical engineering bicssc / Medicine - general issues bicssc / Life sciences - general issues bicssc / Medical physics bicssc / Medical imaging bicssc / Oncology bisacsh / MEDICAL / Oncology / General bisacsh / SCIENCE / Physics / General Bildgebendes Verfahren (DE-588)4006617-4 gnd Bildanalyse (DE-588)4145391-8 gnd |
topic_facet | bicssc / Biomedical engineering bicssc / Medicine - general issues bicssc / Life sciences - general issues bicssc / Medical physics bicssc / Medical imaging bicssc / Oncology bisacsh / MEDICAL / Oncology / General bisacsh / SCIENCE / Physics / General Bildgebendes Verfahren Bildanalyse |
work_keys_str_mv | AT yangxiaofeng medicalimagesynthesismethodsandclinicalapplications |