9783030139711 - deep learning and convolutional neural networks for medical imaging and clinical informatics (14 risultati)
Lingua: Inglese
Editore: Springer, 2020
Serie: Advances in Computer Vision and Pattern Recognition, Libro 71 di 86. Libro 71 di 86 - Advances in Computer Vision and Pattern Recognition
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Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections
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Serie: Advances in Computer Vision and Pattern Recognition, Libro 71 di 86. Libro 71 di 86 - Advances in Computer Vision and Pattern Recognition
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Condizione: New. pp. XI, 461 177 illus., 156 illus. in color. 1st ed. 2019 edition NO-PA16APR2015-KAP.
Lingua: Inglese
Editore: Springer, 2020
Serie: Advances in Computer Vision and Pattern Recognition, Libro 71 di 86. Libro 71 di 86 - Advances in Computer Vision and Pattern Recognition
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Altre immaginiLingua: Inglese
Editore: Springer, 2020
Serie: Advances in Computer Vision and Pattern Recognition, Libro 71 di 86. Libro 71 di 86 - Advances in Computer Vision and Pattern Recognition
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Taschenbuch. Condizione: Neu. Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics | Le Lu (u. a.) | Taschenbuch | Advances in Computer Vision and Pattern Recognition | xi | Englisch | 2020 | Springer | EAN 9783030139711 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergarten…str. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Lingua: Inglese
Editore: Springer, 2020
Serie: Advances in Computer Vision and Pattern Recognition, Libro 71 di 86. Libro 71 di 86 - Advances in Computer Vision and Pattern Recognition
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Da: Mispah books, Redhill, SURRE, Regno UnitoMispah books
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Paperback. Condizione: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
Lingua: Inglese
Editore: Springer, 2020
Serie: Advances in Computer Vision and Pattern Recognition, Libro 71 di 86. Libro 71 di 86 - Advances in Computer Vision and Pattern Recognition
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book reviews the state of the art in deep learning approaches to high-performance robust disease detection, robust and accurate organ segmentation in medical image computing (radiological and pathological imaging modalities), and the construc…tion and mining of large-scale radiology databases. It particularly focuses on the application of convolutional neural networks, and on recurrent neural networks like LSTM, using numerous practical examples to complement the theory.The book's chief features are as follows: It highlights how deep neural networks can be used to address new questions and protocols, and to tackle current challenges in medical image computing; presents a comprehensive review of the latest research and literature; and describes a range of different methods that employ deep learning for object or landmark detection tasks in 2D and 3D medical imaging. In addition, the book examines a broad selection of techniques for semantic segmentation using deep learning principles in medical imaging; introduces a novel approach to text and image deep embedding for a large-scale chest x-ray image database; and discusses how deep learning relational graphs can be used to organize a sizable collection of radiology findings from real clinical practice, allowing semantic similarity-based retrieval.The intended reader of this edited book is a professional engineer, scientist or a graduate student who is able to comprehend general concepts of image processing, computer vision and medical image analysis. They can apply computer science and mathematical principles into problem solving practices. It may be necessary to have a certain level of familiarity with a number of more advanced subjects: image formation and enhancement, image understanding, visual recognition in medical applications, statistical learning, deep neural networks, structured prediction and image segmentation.
Lingua: Inglese
Editore: Springer, 2020
Serie: Advances in Computer Vision and Pattern Recognition, Libro 71 di 86. Libro 71 di 86 - Advances in Computer Vision and Pattern Recognition
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Da: Kennys Bookstore, Olney, MD, U.S.A.Kennys Bookstore
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Serie: Advances in Computer Vision and Pattern Recognition, Libro 71 di 86. Libro 71 di 86 - Advances in Computer Vision and Pattern Recognition
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Lingua: Inglese
Editore: Springer, 2020
Serie: Advances in Computer Vision and Pattern Recognition, Libro 71 di 86. Libro 71 di 86 - Advances in Computer Vision and Pattern Recognition
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Da: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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Condizione: new. Questo è un articolo print on demand.
Lingua: Inglese
Editore: Springer International Publishing, 2020
Serie: Advances in Computer Vision and Pattern Recognition, Libro 71 di 86. Libro 71 di 86 - Advances in Computer Vision and Pattern Recognition
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Da: moluna, Greven, Germaniamoluna
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Reviews the state of the art in deep learning approaches to robust disease detection, organ segmentation in medical image computing, and the construction and mining of large-scale radiology databasesParticularly focu…ses on the application of convo.
Lingua: Inglese
Editore: Springer International Publishing Okt 2020, 2020
Serie: Advances in Computer Vision and Pattern Recognition, Libro 71 di 86. Libro 71 di 86 - Advances in Computer Vision and Pattern Recognition
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book reviews the state of the art in deep learning approaches to high-performance robust disease detection, robust and accurate organ segmentation in medical image computing (radiological and pathological imaging modalities),…and the construction and mining of large-scale radiology databases. It particularly focuses on the application of convolutional neural networks, and on recurrent neural networks like LSTM, using numerous practical examples to complement the theory.The book's chief features are as follows: It highlights how deep neural networks can be used to address new questions and protocols, and to tackle current challenges in medical image computing; presents a comprehensive review of the latest research and literature; and describes a range of different methods that employ deep learning for object or landmark detection tasks in 2D and 3D medical imaging. In addition, the book examines a broad selection of techniques for semantic segmentation using deep learning principles in medical imaging; introduces a novel approach to text and image deep embedding for a large-scale chest x-ray image database; and discusses how deep learning relational graphs can be used to organize a sizable collection of radiology findings from real clinical practice, allowing semantic similarity-based retrieval.The intended reader of this edited book is a professional engineer, scientist or a graduate student who is able to comprehend general concepts of image processing, computer vision and medical image analysis. They can apply computer science and mathematical principles into problem solving practices. It may be necessary to have a certain level of familiarity with a number of more advanced subjects: image formation and enhancement, image understanding, visual recognition in medical applications, statistical learning, deep neural networks, structured prediction and image segmentation. 476 pp. Englisch.
Lingua: Inglese
Editore: Springer, 2020
Serie: Advances in Computer Vision and Pattern Recognition, Libro 71 di 86. Libro 71 di 86 - Advances in Computer Vision and Pattern Recognition
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Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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Condizione: New. Print on Demand pp. XI, 461 177 illus., 156 illus. in color.
Lingua: Inglese
Editore: Springer, Springer Okt 2020, 2020
Serie: Advances in Computer Vision and Pattern Recognition, Libro 71 di 86. Libro 71 di 86 - Advances in Computer Vision and Pattern Recognition
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Chapter 1. Clinical Report Guided Multi-Sieving Deep Learning for Retinal Microaneurysm Detection.- Chapter 2. Optic Disc and Cup Segmentation Based on Multi-label Deep Network for Fundus Glaucoma Screening.- Chapter 3. Thoracic Diseas…e Identification and Localization with Limited Supervision.- Chapter 4. ChestX-ray8: Hospital-scale Chest X-ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseases.- Chapter 5. TieNet: Text-Image Embedding Network for Common Thorax Disease Classification and Reporting in Chest X-rays.- Chapter 6. Deep Lesion Graph in the Wild: Relationship Learning and Organization of Significant Radiology Image Findings in a Diverse Large-scale Lesion Database.- Chapter 7. Deep Reinforcement Learning based Attention to Detect Breast Lesions from DCE-MRI.- Chapter 8. Deep Convolutional Hashing for Low Dimensional Binary Embedding of Histopathological Images.- Chapter 9. Pancreas Segmentation in CT and MRI Images via Domain Specific Network Designing and Recurrent Neural Contextual Learning.- Chapter 10. Spatial Clockwork Recurrent Neural Network for Muscle Perimysium Segmentation.- Chapter 11. Pancreas.- Chapter 12. Multi-Organ.- Chapter 13. Convolutional Invasion and Expansion Networks for Tumor Growth Prediction.- Chapter 14. Cross-Modality Synthesis in Magnetic Resonance Imaging.- Chapter 15. Image Quality Assessment for Population Cardiac MRI.- Chapter 16. Low Dose CT Image Denoising Using a Generative Adversarial Network with Wasserstein Distance and Perceptual Loss.- Chapter 17. Unsupervised Cross-Modality Domain Adaptation of ConvNets for Biomedical Image Segmentations with Adversarial Loss.- Chapter 18. Automatic Vertebra Labeling in Large-Scale Medical Images using Deep Image-to-Image Network with Message Passing and Sparsity Regularization.- Chapter 19. 3D Anisotropic Hybrid Network: Transferring Convolutional Features from 2D Images to 3D Anisotropic Volumes.- Chapter 20. Multi-Agent Learning for Robust Image Registration.- Chapter 21. Deep Learning in Magnetic Resonance Imaging of Cardiac Function.- Chapter 22. Automatic Vertebra Labeling in Large-Scale Medical Images using Deep Image-to-Image Network with Message Passing and Sparsity Regularization.- Chapter 23. Deep Learning on Functional Connectivity of Brain: Are We There Yet .Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 476 pp. Englisch.
Lingua: Inglese
Editore: Springer, 2020
Serie: Advances in Computer Vision and Pattern Recognition, Libro 71 di 86. Libro 71 di 86 - Advances in Computer Vision and Pattern Recognition
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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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Condizione: New. PRINT ON DEMAND pp. XI, 461 177 illus., 156 illus. in color.
