Deep Network Design for Medical Image Computing : Principles and Applications
Deep Network Design for Medical Image Computing: Principles and Applications covers a range of MIC tasks and discusses design principles of these tasks for deep learning approaches in medicine. These include skin disease classification, vertebrae identification and localization, cardiac ultrasound i...
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| Autors principals: | , , |
|---|---|
| Format: | Livre numérique |
| Idioma: | Anglais |
| Publicat: |
San Diego, CA :
Elsevier Science
2022.
Paris : Cyberlibris |
| Accés en línia: | Accès Université d'Orléans et IFPM |
| Nota: |
Couverture. https://static2.cyberlibris.com/books_upload/136pix/9780128244036.jpg Cyberlibris (ScholarVox) corpus Informatique |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Deep Network Design for Medical Image Computing, Principles and Applications, Haofu Liao, S. Kevin Zhou, Jiebo Luo, San Diego, CA, Elsevier Science, 2022, 1 vol. (380 p.), 978-01-2824-383-1 |
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| 100 | 1 | |a Liao, Haofu. | |
| 245 | 1 | 0 | |a Deep Network Design for Medical Image Computing : |b Principles and Applications |c Haofu Liao, S. Kevin Zhou, Jiebo Luo. |
| 260 | |a San Diego, CA : |b Elsevier Science. | ||
| 260 | |a Paris : |b Cyberlibris, |c 2022. | ||
| 500 | |a Couverture. https://static2.cyberlibris.com/books_upload/136pix/9780128244036.jpg | ||
| 500 | |a Cyberlibris (ScholarVox) corpus Informatique | ||
| 506 | |a L'accès en ligne est réservé aux établissements ou bibliothèques ayant souscrit l'abonnement. Cyberlibris | ||
| 520 | |a Deep Network Design for Medical Image Computing: Principles and Applications covers a range of MIC tasks and discusses design principles of these tasks for deep learning approaches in medicine. These include skin disease classification, vertebrae identification and localization, cardiac ultrasound image segmentation, 2D/3D medical image registration for intervention, metal artifact reduction, sparse-view artifact reduction, etc. For each topic, the book provides a deep learning-based solution that takes into account the medical or biological aspect of the problem and how the solution addresses a variety of important questions surrounding architecture, the design of deep learning techniques, when to introduce adversarial learning, and more. This book will help graduate students and researchers develop a better understanding of the deep learning design principles for MIC and to apply them to their medical problems. Explains design principles of deep learning techniques for MIC Contains cutting-edge deep learning research on MIC Covers a broad range of MIC tasks, including the classification, detection, segmentation, registration, reconstruction and synthesis of medical images | ||
| 700 | 1 | |a Zhou, S. Kevin. |4 aut | |
| 700 | 1 | |a Luo, Jiebo. |4 aut | |
| 776 | 0 | |t Deep Network Design for Medical Image Computing |o Principles and Applications |f Haofu Liao, S. Kevin Zhou, Jiebo Luo |c San Diego, CA |n Elsevier Science |d 2022 |p 1 vol. (380 p.) |z 978-01-2824-383-1 | |
| 856 | 4 | |5 452349901:845628399 |u https://ezproxy.univ-orleans.fr/login?url=https://univ.scholarvox.com/book/88955560 |z Accès Université d'Orléans et IFPM | |
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