Description

Book Synopsis


Table of Contents
1. An Introduction to Neural Networks and Deep Learning 2. Deep reinforcement learning in medical imaging 3. CapsNet for medical image segmentation 4.Transformer for Medical Image Analysis 5. An overview of disentangled representation learning for MR images 6. Hypergraph Learning and Its Applications for Medical Image Analysis 7. Unsupervised Domain Adaptation for Medical Image Analysis 8. Medical image synthesis and reconstruction using generative adversarial networks 9. Deep Learning for Medical Image Reconstruction 10. Dynamic inference using neural architecture search in medical image segmentation 11. Multi-modality cardiac image analysis with deep learning 12. Deep Learning-based Medical Image Registration 13. Data-driven learning strategies for biomarker detection and outcome prediction in Autism from task-based fMRI 14. Deep Learning in Functional Brain Mapping and associated applications 15. Detecting, Localising, and Classifying Polyps from Colonoscopy Videos Using Deep Learning 16. OCTA Segmentation with limited training data using disentangled represenatation learning 17. Considerations in the Assessment of Machine Learning Algorithm Performance for Medical Imaging

Deep Learning for Medical Image Analysis

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    £89.96

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    RRP £99.95 – you save £9.99 (9%)

    Order before 4pm tomorrow for delivery by Mon 27 Jul 2026.

    A Paperback by Hayit Greenspan, Dinggang Shen

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      Publisher: Elsevier Science
      Publication Date: Publication Date: 11/27/2023 12:00:00 AM
      ISBN13: 9780323851244, 978-0323851244
      ISBN10: 032385124X

      Description

      Book Synopsis


      Table of Contents
      1. An Introduction to Neural Networks and Deep Learning 2. Deep reinforcement learning in medical imaging 3. CapsNet for medical image segmentation 4.Transformer for Medical Image Analysis 5. An overview of disentangled representation learning for MR images 6. Hypergraph Learning and Its Applications for Medical Image Analysis 7. Unsupervised Domain Adaptation for Medical Image Analysis 8. Medical image synthesis and reconstruction using generative adversarial networks 9. Deep Learning for Medical Image Reconstruction 10. Dynamic inference using neural architecture search in medical image segmentation 11. Multi-modality cardiac image analysis with deep learning 12. Deep Learning-based Medical Image Registration 13. Data-driven learning strategies for biomarker detection and outcome prediction in Autism from task-based fMRI 14. Deep Learning in Functional Brain Mapping and associated applications 15. Detecting, Localising, and Classifying Polyps from Colonoscopy Videos Using Deep Learning 16. OCTA Segmentation with limited training data using disentangled represenatation learning 17. Considerations in the Assessment of Machine Learning Algorithm Performance for Medical Imaging

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