Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics

Lingua: inglese

Editore: Springer, Springer Okt 2020, 2020

3030139719 / 9783030139711

Serie: Libro 71 di 86 - Advances in Computer Vision and Pattern Recognition

Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000

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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 Disease 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.

Codice articolo 9783030139711

Titolo
Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics
Autore
Le Lu
Editore
Springer, Springer Okt 2020
Anno di pubblicazione
2020
Condizione
Neu
Rilegatura
Taschenbuch
Lingua
inglese
ISBN 10
3030139719
ISBN 13
9783030139711
Peso dell'articolo
715 grammi
Dimensioni
235x155x26 mm
Serie
Libro 71 di 86: Advances in Computer Vision and Pattern Recognition

buchversandmimpf2000

Emtmannsberg, BAYE, Germania

Venditore con 5 stelle

Venditore AbeBooks dal 23 gennaio 2017

Tariffe di spedizione da Germania a U.S.A.

ArticoloDa 60 a 60 giorni lavorativiDa 60 a 60 giorni lavorativi
Primo articoloEUR 60,00EUR 75,00
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Impressum Thorsten Retsch Buchversand Mimpf2000 Oberölschnitz 16 95517 Emtmannsberg Deutschland Telefon: 09209-2023188 Email: mimpf2000@online.de USt-ID-Nr.: DE 235096871 Wir führen gebrauchte Bücher aus allen Sparten der Literatur

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