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This unique text/reference highlights a selection of practical applications of advanced image analysis methods for medical images. The book covers the complete methodology for processing, analysing and interpreting diagnostic results of sample CT images. The text also presents significant problems related to new approaches and paradigms in image understanding and semantic image analysis. To further engage the reader, example source code is provided for the implemented algorithms in the described solutions. Features: describes the most important methods and algorithms used for image analysis; examines the fundamentals of cognitive computer image analysis for computer-aided diagnosis and semantic image description; presents original approaches for the semantic analysis of CT perfusion and CT angiography images of the brain and carotid artery; discusses techniques for creating 3D visualisations of large datasets; reviews natural user interfaces in medical imaging systems, including GDL technology.
Presenting a series of research papers on image processing and communications, this book not only provides a summary of currently available technologies but also outlines potential future solutions in these areas. Gathering the proceedings of the 9th International Conference on Image Processing and Communications (IP&C 2017), held in Bydgoszcz, Poland, on September 13–14, 2017, the book is divided into three parts. Part I addresses image processing, offering a comprehensive survey of different methods of image processing and discussing computer vision. In turn, Part II presents novel works in algorithms and methods and showcases formal and practical advances. Lastly, Part III examines networks, communications and a diverse range of applications.
This book describes important methodologies, tools and techniques from the fields of artificial intelligence, basically those which are based on relevant conceptual and formal development. The coverage is wide, ranging from machine learning to the use of data on the Semantic Web, with many new topics. The contributions are concerned with machine learning, big data, data processing in medicine, similarity processing in ontologies, semantic image analysis, as well as many applications including the use of machine leaning techniques for cloud security, artificial intelligence techniques for detecting COVID-19, the Internet of things, etc. The book is meant to be a very important and useful source of information for researchers and doctoral students in data analysis, Semantic Web, big data, machine learning, computer engineering and related disciplines, as well as for postgraduate students who want to integrate the doctoral cycle.
Over the decades, the fields of health information systems and informatics have seen rapid growth. Such integrative efforts within the two disciplines have resulted in emerging innovations within the realm of medicine and healthcare. The Handbook of Research on Emerging Perspectives on Healthcare Information Systems and Informatics provides emerging research on the innovative practices of information systems and informatic software in providing efficient, safe, and impactful healthcare systems. While highlighting topics such as conceptual modeling, surveillance data, and decision support systems, this handbook explores the applications and advancements in technological adoption and application of information technology in health institutions. This publication is a vital resource for hospital administrators, healthcare professionals, researchers, and practitioners seeking current research on health information systems in the digital era.
Cognitive impairment, through Alzheimer’s disease or other related forms of dementia, is a serious concern for afflicted individuals and their caregivers. Understanding patients’ mental states and combatting social stigmas are important considerations in caring for cognitively impaired individuals. Technology is playing an increasing role in the lives of the elderly. One of the most prevalent developments for the aging population is the use of technological innovations for intervention and treatment of individuals with mental impairments. Research Anthology on Diagnosing and Treating Neurocognitive Disorders examines the treatment, diagnosis, prevention, and therapeutic and technological interventions of neurodegenerative disorders. It also describes programs and strategies that professional and family caregivers can implement to engage and improve the quality of life of persons suffering from cognitive impairment. Highlighting a range of topics such as dementia, subjective wellbeing, and cognitive decline, this publication is an ideal reference source for speech pathologists, social workers, occupational therapists, psychologists, psychiatrists, neurologists, pediatricians, researchers, clinicians, and academicians seeking coverage on neurocognitive disorder identification and strategies for clinician support and therapies.
Medical imaging has transformed the ways in which various conditions, injuries, and diseases are identified, monitored, and treated. As various types of digital visual representations continue to advance and improve, new opportunities for their use in medical practice will likewise evolve. Medical Imaging: Concepts, Methodologies, Tools, and Applications presents a compendium of research on digital imaging technologies in a variety of healthcare settings. This multi-volume work contains practical examples of implementation, emerging trends, case studies, and technological innovations essential for using imaging technologies for making medical decisions. This comprehensive publication is an essential resource for medical practitioners, digital imaging technologists, researchers, and medical students.
The four-volume set LNCS 14442 -14445 constitutes the proceedings of the 19th IFIP TC 13 International Conference on Human-Computer Interaction, INTERACT 2023, held in York, UK, in August/September 2023. The 71 full papers and 58 short papers included in this book were carefully reviewed and selected from 406 submissions. They were organized in topical sections as follows: 3D Interaction; Accessibility; Accessibility and Aging; Accessibility for Auditory/Hearing Disabilities; Co-Design; Cybersecurity and Trust; Data Physicalisation and Cross-device; Eye-Free, Gesture Interaction and Sign Language; Haptic interaction and Healthcare applications; Self-Monitoring; Human-Robot Interaction; Information Visualization; Information Visualization and 3D Interaction; Interacting with Children; Interaction with Conversational Agents; Methodologies for HCI; Model-Based UI Design and Testing; Montion Sickness, Stress and Risk perception in 3D Environments and Multisensory interaction; VR experiences; Natural Language Processing and AI Explainability; Online Collaboration and Cooperative work; Recommendation Systems and AI Explainability; Social AI; Social and Ubiquitous Computing; Social Media and Digital Learning; Understanding Users and Privacy Issues; User movement and 3D Environments; User Self-Report; User Studies; User Studies, Eye-Tracking, and Physiological Data; Virtual Reality; Virtual Reality and Training; Courses; Industrial Experiences; Interactive Demonstrations; Keynotes; Panels; Posters; and Workshops.
This book constitutes the refereed proceedings of the workshops held with the 17th International Conference on Image Analysis and Processing, ICIAP 2013, held in Naples, Italy, in September 2013. The proceedings include papers from the five individual workshops focusing on topics of interest to the pattern recognition, image analysis, and computer vision communities, exploring emergent research directions or spotlight cross-disciplinary links with related fields and / or application areas.
Advanced techniques in image processing have led to many innovations supporting the medical field, especially in the area of disease diagnosis. Biomedical imaging is an essential part of early disease detection and often considered a first step in the proper management of medical pathological conditions. Classification and Clustering in Biomedical Signal Processing focuses on existing and proposed methods for medical imaging, signal processing, and analysis for the purposes of diagnosing and monitoring patient conditions. Featuring the most recent empirical research findings in the areas of signal processing for biomedical applications with an emphasis on classification and clustering techniques, this essential publication is designed for use by medical professionals, IT developers, and advanced-level graduate students.