With the technology innovations dentistry has witnessed in all its branches over the past three decades, the need for more precise diagnostic tools and advanced imaging methods has become mandatory across the industry. Recent advancements to imaging systems are playing an important role in efficient diagnoses, treatments, and surgeries. Computational Techniques for Dental Image Analysis provides innovative insights into computerized methods for automated analysis. The research presented within this publication explores pattern recognition, oral pathologies, and diagnostic processing. It is designed for dentists, professionals, medical educators, medical imaging technicians, researchers, oral surgeons, and students, and covers topics centered on easier assessment of complex cranio-facial tissues and the accurate diagnosis of various lesions at early stages.

Medical imaging provides medical professionals the unique ability to investigate and diagnose injuries and illnesses without being intrusive. With the surge of technological advancement in recent years, the practice of medical imaging has only been improved through these technologies and procedures. It is essential to examine these innovations in medical imaging to implement and improve the practice around the world. The Research Anthology on Improving Medical Imaging Techniques for Analysis and Intervention investigates and presents the recent innovations, procedures, and technologies implemented in medical imaging. Covering topics such as automatic detection, simulation in medical education, and neural networks, this major reference work is an excellent resource for radiologists, medical professionals, hospital administrators, medical educators and students, librarians, researchers, and academicians.

As the healthcare industry continues to expand, it must utilize technology to ensure efficiencies are maintained. Healthcare needs to move in a direction where computational methods and algorithms can relieve the routine work of medical doctors, leaving them more time to carry out more important and skilled tasks such as surgery. Computational Methods and Algorithms for Medicine and Optimized Clinical Practice discusses some of the most interesting aspects of theoretical and applied research covering complementary facets of computational methods and algorithms to achieve greater efficiency and support medical personnel. Featuring research on topics such as healthcare reform, artificial intelligence, and disease detection, this book will particularly appeal to medical professionals and practitioners, hospitals, administrators, students, researchers, and academicians.

The variety and abundance of qualitative characteristics of agricultural products have been the main reasons for the development of different types of non-destructive methods (NDTs). Quality control of these products is one of the most important tasks in manufacturing processes. The use of control and automation has become more widespread, and new approaches provide opportunities for production competition through new technologies. Applications of Image Processing and Soft Computing Systems in Agriculture examines applications of artificial intelligence in agriculture and the main uses of shape analysis on agricultural products such as relationships between form and genetics, adaptation, product characteristics, and product sorting. Additionally, it provides insights developed through computer vision techniques. Highlighting such topics as deep learning, agribusiness, and augmented reality, it is designed for academicians, researchers, agricultural practitioners, and industry professionals.

Medical and information communication technology professionals are working to develop robust classification techniques, especially in healthcare data/image analysis, to ensure quick diagnoses and treatments to patients. Without fast and immediate access to healthcare databases and information, medical professionals’ success rates and treatment options become limited and fall to disastrous levels. Advanced Classification Techniques for Healthcare Analysis provides emerging insight into classification techniques in delivering quality, accurate, and affordable healthcare, while also discussing the impact health data has on medical treatments. Featuring coverage on a broad range of topics such as early diagnosis, brain-computer interface, metaheuristic algorithms, clustering techniques, learning schemes, and mobile telemedicine, this book is ideal for medical professionals, healthcare administrators, engineers, researchers, academicians, and technology developers seeking current research on furthering information and communication technology that improves patient care.

Along with the introduction of technology in nearly every facet of human life comes the question of the ethical side of using technology to improve the human condition, whether that be physically or mentally. The capabilities of human enhancement technologies have created a dual-sided approach to discussing human enhancement: the critical approach of attempting to reach human perfection and the ethics within that idea and the endless capabilities of technology that have greatly impacted the medical field. It is essential to discuss both aspects within these emerging technologies, whether as separate entities or as cohesive units. Ranging from disease detection and treatment to implants and prosthetics to robotics and genetic engineering, human enhancement technologies are widespread and multi-purposed. By going beyond the capabilities of human hands, these technologies have propelled modern medicine and healthcare to new levels that have allowed humans to face new treatments or assistive technologies not seen before. The Research Anthology on Emerging Technologies and Ethical Implications in Human Enhancement covers the primary technologies and tools being used in medicine and healthcare along with discussions on the ethics of enhancing the human body. Topics covered include prosthetics and implants, robotics, human disorders/diseases and treatments and smart technologies, along with law and theory. This publication serves as a valuable reference work for doctors, medical professionals, researchers, students, professionals, and practitioners involved in fields that include ethics, medicine, computer science, robotics, genetics, assistive technologies, nanotechnology, biomedical engineering, and biotechnology.

This book constitutes the refereed proceedings of the Second International Conference, SLAAI-ICAI 2018, held in Moratuwa, Sri Lanka, in December 2018. The 32 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in the following topical sections: ​intelligence systems; neural networks; game theory; ontology engineering; natural language processing; agent based system; signal and image processing.

Optimized linear algebra (LA) libraries that are able to exploit the underlying hardware are always of interest in the high-performance computing community. The implementation of LA software has evolved along with computer architecture, while the specification remains unaltered almost from the beginning. It is important to differentiate between the specification of LA libraries and their implementation. Because LA libraries pursue high performance, the implementation for a given architecture needs to be optimized for it specifically. However, the type of operations included in the libraries, the input/output parameters, and the data types to be handled are common to all of them. This is why, while the specification remains constant, the implementation evolves with the creation of new architectures. Developing Linear Algebra Codes on Modern Processors: Emerging Research and Opportunities presents the main characteristics of LA libraries, showing the differences between the standards for sparse and dense versions. It further explores relevant linear algebra problems and shows, in a clear and understandable way, how to solve them using different computer architectures. Covering topics such as programming models, batched computing, and distributed memory platforms, this premier reference source is an excellent resource for programmers, computer scientists, engineers, students and faculty of higher education, librarians, researchers, and academicians.

While doctors and physicians are more than capable of detecting diseases of the brain, the most agile human mind cannot compete with the processing power of modern technology. Utilizing algorithmic systems in healthcare in this way may provide a way to treat neurological diseases before they happen. Early Detection of Neurological Disorders Using Machine Learning Systems provides innovative insights into implementing smart systems to detect neurological diseases at a faster rate than by normal means. The topics included in this book are artificial intelligence, data analysis, and biomedical informatics. It is designed for clinicians, doctors, neurologists, physiotherapists, neurorehabilitation specialists, scholars, academics, and students interested in topics centered on biomedical engineering, bio-electronics, medical electronics, physiology, neurosciences, life sciences, and physics.

This book provides an overview of computational approaches to medical image examination and analysis in oral radiology, utilizing dental radiograph to detect and diagnose dental caries in cases of decayed teeth. Coverage includes basic image processing techniques; approaches for Region of Interest extraction and analysis; and the role of computational clustering techniques for segmentation of teeth and dental caries. The book also presents a novel multiphase level set method for automatic segmentation of dental radiographs.