In den letzten Jahren hat sich der Workshop "Bildverarbeitung fur die Medizin" durch erfolgreiche Veranstaltungen etabliert. Ziel ist auch 2017 wieder die Darstellung aktueller Forschungsergebnisse und die Vertiefung der Gesprache zwischen Wissenschaftlern, Industrie und Anwendern. Die Beitrage dieses Bandes - einige davon in englischer Sprache - umfassen alle Bereiche der medizinischen Bildverarbeitung, insbesondere Bildgebung und -akquisition, Maschinelles Lernen, Bildsegmentierung und Bildanalyse, Visualisierung und Animation, Zeitreihenanalyse, Computerunterstutzte Diagnose, Biomechanische Modellierung, Validierung und Qualitatssicherung, Bildverarbeitung in der Telemedizin u.v.m.

This book constitutes the thoroughly refereed post-workshop proceedings of the 6th International Workshop on Statistical Atlases and Computational Models of the Heart: Imaging and Modelling Challenges, STACOM 2015, held in conjunction with MICCAI 2015, in Munich, Germany, in October 2015. The 23 revised full workshop papers were carefully reviewed and selected from 34 submissions. The papers cover a wide range of topics such cardiac image processing, atlas construction, statistical modeling of cardiac function across different patient populations, cardiac mapping, cardiac computational physiology, model customization, image-based modelling and image-guided interventional procedures, atlas based functional analysis, ontological schemata for data and results, integrated functional and structural analysis.

This book constitutes the thoroughly refereed post-conference proceedings of the International Conference for Smart Health, ICSH 2015, held in Phoenix, AZ, USA, in November 2015. The 33 papers presented together were carefully reviewed and selected from 43 submissions. The conference focused on topics and issues including medical monitoring and information extraction, clinical and medical data mining, health data analysis and management, big data and smart health, and healthcare intelligent systems and clinical practice.

Have you ever experienced the burden of an adverse event or a near-miss in healthcare and wished there was a way to mitigate it? This book walks you through a classic adverse event as a case study and shows you how. It is a practical guide to continuously improving your healthcare environment, processes, tools, and ultimate outcomes, through the discipline of human factors. Using this book, you as a healthcare professional can improve patient safety and quality of care. Adverse events are a major concern in healthcare today. As the complexity of healthcare increases-with technological advances and information overload-the field of human factors offers practical approaches to understand the situation, mitigate risk, and improve outcomes. The first part of this book presents a human factors conceptual framework, and the second part offers a systematic, pragmatic approach. Both the framework and the approach are employed to analyze and understand healthcare situations, both proactively-for constant improvement-and reactively-learning from adverse events. This book guides healthcare professionals through the process of mapping the environmental and human factors; assessing them in relation to the tasks each person performs; recognizing how gaps in the fit between human capabilities and the demands of the task in the environment have a ripple effect that increases risk; and drawing conclusions about what types of changes facilitate improvement and mitigate risk, thereby contributing to improved healthcare outcomes.

This book constitutes the thoroughly refereed post-workshop proceedings of the 7th International Workshop on Statistical Atlases and Computational Models of the Heart: Imaging and Modelling Challenges. 7th International Workshop, STACOM 2016, Held in conjunction with MICCAI 2016, Athens, Greece, October 17, 2016, Revised Selected papers The 24 revised full workshop papers were carefully reviewed and selected from 32 submissions. The papers cover a wide range of topics such as cardiac image processing; atlas construction, statistical modelling of cardiac function across different patient populations; cardiac mapping, cardiac computational physiology; model customization; image-based modelling and image-guided interventional procedures; atlas based functional analysis, ontological schemata for data and results; integrated functional and structural analyses; pre-clinical and clinical applicability of the methods described.

The 6th International Conference on Medical Imaging and Augmented Reality, MIAR 2016, was held in Bern, Switzerland during August 2016. The aim of MIAR is to bring together researchers in computer vision, graphics, robotics, and medical imaging to present the state-of-the-art developments in this ever-growing research area in topics such as: Medical Image Formation, Analysis and Interpretation Augmented Reality, Visualization and Simulation Computer Assisted Interventional and Robotics, Surgical Planning Systematic Extra- and Intra-corporeal Imaging Modalities General Biological and Neuroscience Image Computing

The two volume set LNAI 9413 + 9414 constitutes the proceedings of the 14th Mexican International Conference on Artificial Intelligence, MICAI 2015, held in Cuernavaca,. Morelos, Mexico, in October 2015. The total of 98 papers presented in these proceedings was carefully reviewed and selected from 297 submissions. They were organized in topical sections named: natural language processing; logic and multi-agent systems; bioinspired algorithms; neural networks; evolutionary algorithms; fuzzy logic; machine learning and data mining; natural language processing applications; educational applications; biomedical applications; image processing and computer vision; search and optimization; forecasting; and intelligent applications.

This book constitutes the refereed post-conference proceedings of the First International Workshop on Spectral and Shape Analysis in Medical Imaging, SeSAMI 2016, held in conjunction with MICCAI 2016, in Athens, Greece, in October 2016. The 10 submitted full papers presented in this volume were carefully reviewed. The papers reflect the following topics: spectral methods; longitudinal methods; and shape methods.

This book constitutes the revised selected papers from the 5th International Workshop on Clinical Image-Based Procedures, CLIP 2016, held in conjunction with MICCAI 2016 in Athens, Greece, in October 2016. The 10 papers presented in this volume were carefully reviewed and selected from 16 submissions. Specific topics include various image segmentation and registration techniques, applied to various parts of the body. They range from interventional planning to navigation of devices and navigation to the anatomy of interest. Clinical applications cover the skull, the cochlea, cranial nerves, the aortic valve, wrists, and the abdomen, among others.

This book constitutes the refereed proceedings of the 5th International Conference on Health Information Science, HIS 2016, held in Shanghai, China, in November 2016. The 13 full papers and 9 short papers presented were carefully reviewed and selected from numerous submissions. The scope of the papers includes medical/health/biomedicine information resources such as patient medical records, devices and equipments, software and tools to capture, store, retrieve, process, analyze, and optimize the use of information in the health domain; data management, data mining, and knowledge discovery, all of which play a key role in decision making, management of public health, examination of standards, privacy and security issues; computer visualization and artificial intelligence for computer aided diagnosis; development of new architectures and applications for health information systems.

This book introduces the field of Health Web Science and presents methods for information gathering from written social media data. It explores the availability and utility of the personal medical information shared on social media platforms and determines ways to apply this largely untapped information source to healthcare systems and public health monitoring. Introducing an innovative concept for integrating social media data with clinical data, it addresses the crucial aspect of combining experiential data from social media with clinical evidence, and explores how the variety of available social media content can be analyzed and implemented. The book tackles a range of topics including social media's role in healthcare, the gathering of shared information, and the integration of clinical and social media data. Application examples of social media for health monitoring, along with its usage in patient treatment are also provided. The book also considers the ethical and legal issues of gathering and utilizing social media data, along with the risks and challenges that must be considered when integrating social media data into healthcare choices. With an increased interest internationally in E-Health, Health 2.0, Medicine 2.0 and the recent birth of the discipline of Web Science, this book will be a valuable resource for researchers and practitioners investigating this emerging topic.

This book constitutes the refereed proceedings of the 7th International Workshop on Machine Learning in Medical Imaging, MLMI 2016, held in conjunction with MICCAI 2016, in Athens, Greece, in October 2016. The 38 full papers presented in this volume were carefully reviewed and selected from 60 submissions. The main aim of this workshop is to help advance scientific research within the broad field of machine learning in medical imaging. The workshop focuses on major trends and challenges in this area, and presents works aimed to identify new cutting-edge techniques and their use in medical imaging.

This book constitutes the refereed proceedings of the International Conference on Brain and Health Informatics, BHI 2016, held in Omaha, USA, in October 2016. The 37 revised full papers, including two workshop papers from BAI 2016, presented were carefully reviewed and selected for inclusion in the book. The papers are organized in topical sections on cognitive and computational foundations of brain science; investigations of human information processing systems; brain big data analytics, curation and management; new methodologies for brain and mental health; brain-inspired intelligence and computing; brain and artificial intelligence.

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.

This book constitutes the refereed proceedings of the 7th International Conference on Information Technology in Bio- and Medical Informatics, ITBAM 2016, held in Porto, Portugal, in September 2016, in conjunction with DEXA 2016. The 9 revised long papers presented together with 11 poster papers were carefully reviewed and selected from 26 submissions. The papers address the following topics: biomedical data analysis and warehousing; information technologies in brain science; and social networks and process analysis in biomedicine.

This book defines the phenomenon of mHealth and its evolution, explaining why an understanding of mHealth is critical for decision makers, entrepreneurs and policy analysts who are pivotal to developing products that meet the collaborative health information needs of consumers and providers in a competitive and rapidly-changing environment. The book examines trends in mHealth and discusses how mHealth technologies offer opportunities for innovators and entrepreneurs, those who often are industry first-movers with regard to technology advancement. It also explores the changing dynamics and relationships among physicians, patients, insurers, regulators, managers, administrators, caregivers and others involved in the delivery of health services. The primary focus is on the ways in which mHealth technologies are revising and reshaping healthcare delivery systems in the United States and globally and how those changes are expected to change the ways in which the business of healthcare is conducted. mHealth: Transforming Healthcare consists of nine chapters that addresses key content areas, including history (to the extent that dynamic technologies have a history), projection of immediate evolution and consistent issues associated with health technology, such as security and information privacy and government and industry regulation. A major point of discussion addressed is whether mHealth is a transient group of products and a passing patient encounter approach, or if it is the way much of our health care will be delivered in future years with incremental evolution to achieve sustainable innovation of health technologies.

This contributed volume draws a vital picture of the health care sector, which, like no other is affected by technology push and stakeholder pull. Innovative product and service solutions emerge, which have to integrate different stakeholders' interests. This book studies current challenges in health care management from different perspectives. Research articles analyze the situation in the health care sector and present solutions in the following areas: the health care system; hospitals; teams in health care; patients' perspectives; assessment of technologies and innovations; and toolkits for organizing health care. All these contributions summarize pressing hot topics in the health care sector, analyze their future potential, and derive managerial implications. Outstanding best practices throughout Europe are presented in the case study section of the book. Consequently, the book closes the gap between science and practical application by addressing not only readers from academia but also practitioners working in the health care industry.

This book constitutes the proceedings of the 11th International Conference on Data Integration in the Life Sciences, DILS 2015, held in Los Angeles, CA, USA, in July 2015. The 24 papers presented in this volume were carefully reviewed and selected from 40 submissions. They are organized in topical sections named: data integration technologies; ontology and knowledge engineering for data integration; biomedical data standards and coding; medical research applications; and graduate student consortium.

This book discusses the latest advances in human factors and ergonomics, focusing on methods for improving quality, safety, efficiency, and effectiveness in patient care. By emphasizing the physical, cognitive and organizational aspects of human factors and ergonomics applications, it reports on various perspectives, including those of clinicians, patients, health organizations and insurance providers. The book describes cutting-edge applications, highlighting the best practices of staff interactions with patients, as well as interactions with computers and medical devices. It also presents new findings related to improved organizational outcomes in healthcare settings, and approaches to modeling and analysis specifically targeting those work aspects unique to healthcare. Based on the AHFE 2016 International Conference on Human Factors and Ergonomics in Healthcare, held on July 27-31, 2016, in Walt Disney World (R), Florida, USA, the book is intended as timely reference guide for both researchers involved in the design of healthcare systems and devices and healthcare professionals aiming at effective and safe health service delivery. Moreover, by providing a useful survey of cutting-edge methods for improving organizational outcomes in healthcare settings, the book also represents an inspiring reading for healthcare counselors and international health organizations.

This book constitutes the refereed proceedings of the 5th International Conference on Information Technology in Bio- and Medical Informatics, ITBAM 2014, held in Munich, Germany, in September 2014, in conjunction with DEXA 2014. The 9 revised long papers presented together with 3 short papers were carefully reviewed and selected from numerous submissions. The papers address the following topics: clustering and bioinformatics; medical image and data processing; and knowledge discovery and machine learning in medicine.

This book constitutes the thoroughly refereed post-workshop proceedings at PAKDD Workshops 2016, held in conjunction with PAKDD, the 20th Pacific-Asia Conference on Knowledge Discovery and Data Mining in Auckland, New Zealand, in April 2016. The 23 revised papers presented were carefully reviewed and selected from 38 submissions. The workshops affiliated with PAKDD 2016 include: Biologically Inspired Data Mining Techniques, BDM; Machine Learning for Sensory Data Analysis, MLSDA; Predictive Analytics for Critical Care, PACC; as well as Data Mining in Business and Finance, WDMBF.

This book constitutes the refereed proceedings of the 10th International Conference on Persuasive Technology, PERSUASIVE 2015, held in Chicago, IL, USA in June 2015. The 19 revised full papers and 5 revised short papers presented were carefully reviewed and selected from 41 submissions. The papers are grouped in topical sections on understanding individuals, empowering individuals and understanding and empowering communities.

This SpringerBrief addresses the challenges of analyzing multi-relational and noisy data by proposing several Statistical Relational Learning (SRL) methods. These methods combine the expressiveness of first-order logic and the ability of probability theory to handle uncertainty. It provides an overview of the methods and the key assumptions that allow for adaptation to different models and real world applications. The models are highly attractive due to their compactness and comprehensibility but learning their structure is computationally intensive. To combat this problem, the authors review the use of functional gradients for boosting the structure and the parameters of statistical relational models. The algorithms have been applied successfully in several SRL settings and have been adapted to several real problems from Information extraction in text to medical problems. Including both context and well-tested applications, Boosting Statistical Relational Learning from Benchmarks to Data-Driven Medicine is designed for researchers and professionals in machine learning and data mining. Computer engineers or students interested in statistics, data management, or health informatics will also find this brief a valuable resource.

Healthcare has become an extremely important and relevant topic in day to day discussions ever since the COVID-19 pandemic has been encountered by the global population. This has led to a renewed focus and attention that researchers from every discipline have put in to realize better strategies for healthcare management in general. This book is an attempt to put to use recent advancements in the field of the Internet of Medical Things often called IoMT, which is an extension of IoT for real-time, data analytics-driven prompt and quality healthcare to global citizens. Security has been always a challenge with pervasive technologies like IoMT and IoT, and thus usage of disruptive technology like blockchain to offset the security concerns that surround the data and network management. Therefore, this book is an honest attempt to provide directions to applied areas of research in IoMT for healthcare with the aid and help of Blockchain Technologies.

The two volume set LNAI 9413 + LNAI 9414 constitutes the proceedings of the 14th Mexican International Conference on Artificial Intelligence, MICAI 2015, held in Cuernavaca, Morelos, Mexico, in October 2015. The total of 98 papers presented in these proceedings was carefully reviewed and selected from 297 submissions. They were organized in topical sections named: natural language processing; logic and multi-agent systems; bioinspired algorithms; neural networks; evolutionary algorithms; fuzzy logic; machine learning and data mining; natural language processing applications; educational applications; biomedical applications; image processing and computer vision; search and optimization; forecasting; and intelligent applications.