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The Grand Tour
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Time No Longer
Argues that the United States' founding myths no longer apply, and explains why Americans must reconsider the facts of their history.
Deep Learning and Convolutional Neural Networks for Medical Image Computing
This book presents a detailed review of the state of the art in deep learning approaches for semantic object detection and segmentation in medical image computing, and large-scale radiology database mining. A particular focus is placed on the application of convolutional neural networks, with the theory supported by practical examples. Features: highlights how the use of deep neural networks can address new questions and protocols, as well as improve upon existing challenges in medical image computing; discusses the insightful research experience of Dr. Ronald M. Summers; presents a comprehensive review of the latest research and literature; describes a range of different methods that make use of deep learning for object or landmark detection tasks in 2D and 3D medical imaging; examines a varied selection of techniques for semantic segmentation using deep learning principles in medical imaging; introduces a novel approach to interleaved text and image deep mining on a large-scale radiology image database.
Class Actions in Europe
Not so long ago, class actions were considered to be a textbook example of American exceptionalism; many of their main features were assumed to be incompatible with the culture of the civil law world. However, the tide is changing; while there are now trends in the USA toward limiting or excluding class actions, notorious cases like Dieselgate are moving more and more European jurisdictions to extend the reach of their judicial collective redress mechanisms. For many new fans of class actions, collective redress has become a Holy Grail of sorts, a miraculous tool that will rejuvenate national systems of civil justice and grant them unprecedented power. Still, while the introduction of variou...
Deep Learning and Data Labeling for Medical Applications
This book constitutes the refereed proceedings of two workshops held at the 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016, in Athens, Greece, in October 2016: the First Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, LABELS 2016, and the Second International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2016. The 28 revised regular papers presented in this book were carefully reviewed and selected from a total of 52 submissions. The 7 papers selected for LABELS deal with topics from the following fields: crowd-sourcing methods; active learning; transfer learning; semi-supervised learning; and modeling of label uncertainty.The 21 papers selected for DLMIA span a wide range of topics such as image description; medical imaging-based diagnosis; medical signal-based diagnosis; medical image reconstruction and model selection using deep learning techniques; meta-heuristic techniques for fine-tuning parameter in deep learning-based architectures; and applications based on deep learning techniques.
Current Catalog
First multi-year cumulation covers six years: 1965-70.
The Art-journal
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Craniofacial Microsomia and Treacher Collins Syndrome
The book provides a framework for diagnosis and treatment of the complex facial deformities found in craniofacial microsomia and Treacher Collins syndrome. These conditions are difficult to treat due to their complexity and variable presentation. The deformities may be mild or severe and merely cosmetic to life-threatening in nature. These conditions often manifest as complex facial deformities that require multiple surgical interventions. Timing is critical when treating these patients and knowing and choosing the correct operation is key to successful outcomes. This work provides a comprehensive approach in treating these complex patient populations, seeking to answer the following questio...
