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The 18 regular papers presented in this volume were carefully reviewed and selected from 26 submissions. The papers are organized in topical sections on multi-atlas segmentation; segmentation; Alzheimer's disease; reconstruction, denoising, super-resolution; tumor, lesion; and classification, retrival.

This book constitutes the refereed proceedings of the First International Workshop on Connectomics in NeuroImaging, CNI 2017, held in conjunction with MICCAI 2017 in Quebec City, Canada, in September 2017.

The 19 full papers presented were carefully reviewed and selected from 26 submissions. The papers deal with new advancements in network construction, analysis, and visualization techniques in connectomics and their use in clinical diagnosis and group comparison studies as well as in various neuroimaging applications.

This book constitutes the thoroughly refereed post-workshop proceedings of the First International Workshop on Patch-based Techniques in Medical Images, Patch-MI 2015, which was held in conjunction with MICCAI 2015, in Munich, Germany, in October 2015.

The 25 full papers presented in this volume were carefully reviewed and selected from 35 submissions. The topics covered are such as image segmentation of anatomical structures or lesions; image enhancement; computer-aided prognostic and diagnostic; multi-modality fusion; mono and multi modal image synthesis; image retrieval; dynamic,...

This book constitutes the refereed proceedings of the Second International Workshop on Patch-Based Techniques in Medical Images, Patch-MI 2016, which was held in conjunction with MICCAI 2016, in Athens, Greece, in October 2016.

The 17 regular papers presented in this volume were carefully reviewed and selected from 25 submissions.

The main aim of the Patch-MI 2016 workshop is to promote methodological advances within the medical imaging field, with various applications in image segmentation, image denoising, image super-resolution, computer-aided diagnosis, image...

Machine Learning and Medical Imaging presents state-of- the-art machine learning methods in medical image analysis. It first summarizes cutting-edge machine learning algorithms in medical imaging, including not only classical probabilistic modeling and learning methods, but also recent breakthroughs in deep learning, sparse representation/coding, and big data hashing. In the second part leading research groups around the world present a wide spectrum of machine learning methods with application to different medical imaging modalities, clinical domains, and organs.

The...

Yang Guorong is one of the most prominent Chinese philosophers working today and is best known for using the full range of Chinese philosophical resources in connection with the thought of Kant, Hegel, Marx, and Heidegger. In The Mutual Cultivation of Self and Things, Yang grapples with the philosophical problem of how the complexly interwoven nature of things and being relates to human nature, values, affairs, and facts, and ultimately creates a world of meaning. Yang outlines how humans might live more fully integrated lives on philosophical, religious, cultural, aesthetic, and material...

Yang Guorong is one of the most prominent Chinese philosophers working today and is best known for using the full range of Chinese philosophical resources in connection with the thought of Kant, Hegel, Marx, and Heidegger. In The Mutual Cultivation of Self and Things, Yang grapples with the philosophical problem of how the complexly interwoven nature of things and being relates to human nature, values, affairs, and facts, and ultimately creates a world of meaning. Yang outlines how humans might live more fully integrated lives on philosophical, religious, cultural, aesthetic, and material...