Hao Huang – författare
Handbook of Pediatric Brain Imaging
Methods and Applications
1 704 kr
Skickas inom 10-15 vardagar
3 193 kr
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Advanced Materials for Electrochemical Devices discusses the electrochemical basis and application research of various advanced materials of electrochemical devices in the most fundamental perspectives of thermodynamic properties and dynamic behaviors starting from the perspective of material preparation methods. More importantly, the latest scientific research results for each kind of advanced material are also combined to further understand the nature of the materials. Finally, the prediction and evaluation of battery performances as well as the application technologies of various devices are summarized.
This book is divided into four parts to comprehensively and systematically describe the related contents of energy storage materials: Preparation and Electrochemical Fundamentals of Energy Storage Materials (Part I), Electrode Materials of Electrochemical Devices (Part II), Electrolyte and Separator Materials of Electrochemical Devices (Part III), Performance Prediction and Application Technology of Electrochemical Devices (Part IV).
Includes high academic level, wide coverage that is timeless Effectively promotes the development of high-performance devices and industries Provides beginners with the basic knowledge of materials science and electrochemistry, showing them the necessary experimental means for material preparation Serves as a handbook for energy storage material researchers to provide them with appropriate theoretical support and details
Machine Learning in MRI
From Methods to Clinical Translation
1 431 kr
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Machine Learning in MRI: From Methods to Clinical Translation, Volume Thirteen in theAdvances in Magnetic Resonance Technology and Applications series presents state-of-the-art machine learning methods in magnetic resonance imaging that can shape and impact the future of patient treatment and planning. Common methods and strategies along the processing chain of data acquisition, image reconstruction, image post-processing, and image analysis of these imaging modalities are presented and illustrated. The book focuses on applications and anatomies for which machine learning methods can bring, or have already brought. Ideas and concepts on how processing could be harmonized and used to provide deployable frameworks that integrate into the clinical workflows are also considered.Pitfalls and current limitations are discussed in the context of how they could be overcome to cater for clinical needs, making this an ideal reference for medical imaging researchers, industry scientists and engineers, advanced undergraduate and graduate students, and clinicians. By giving an interdisciplinary presentation and discussion on the obstacles and possible solutions for the clinical translation of machine learning methods, this book enables the evolution of machine learning in medical imaging for the next decade.
Brings together applied researchers, clinicians, and computer scientists to give an interdisciplinary perspective on the methods of machine learning in MRI and their potential clinical translationGives a clear presentation of the key concepts of machine learningShows how machine learning methods can be applied to MR image acquisition, MR image reconstruction, MR motion correction, MR image post-processing, and MR image analysisIncludes application chapters that show how the methods can translate into medical practice