Название: Medical Informatics and Bioimaging Using Artificial Intelligence: Challenges, Issues, Innovations and Recent Developments
Автор: Aboul Ella Hassanien, Roheet Bhatnagar, Vaclav Snasel
Издательство: Springer
Серия: Studies in Computational Intelligence
Год: 2022
Страниц: 256
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

This book emphasizes the latest developments and achievements in artificial intelligence and related technologies, focusing on the applications of artificial intelligence and medical diagnosis. The book describes the theory, applications, concept visualization, and critical surveys covering most aspects of AI for medical informatics.

Today, modern societies are witnessing increased usage of technology in almost every domain. Healthcare is one big domain where modern technologies bring a sea change and a paradigm shift in how healthcare is planned, administered, and implemented. Big Data, networking, graphical interfaces, data mining, Machine Learning, pattern recognition, and intelligent decision support systems are a few technologies and research areas currently contributing to medical informatics. Mobility and ubiquity in healthcare systems; physiological and behavioral modeling; standardization of health records, procedures, and technologies; certification; privacy; and security are some of the issues that medical informatics professionals and the Information and Communication Technology (ICT) industry and the research community, in general, are addressing to promote ICT in healthcare further. The assistive technologies and home monitoring applications of ICT have greatly enhanced the quality of life and full integration of all citizens into society.

Bioimaging is a term that covers the complex chain of acquiring, processing, and visualizing structural or functional images of living objects or systems, including extraction and processing of image-related information. Examples of image modalities used in bioimaging are many, including X-ray, CT, MRI and fMRI, PET and HRRT PET, SPECT, MEG, etc. Medical imaging and microscope/fluorescence image processing are important parts of bioimaging referring to the techniques and processes used to create images of the human body, anatomical areas, tissues, and so on, down to the molecular level, for clinical purposes, seeking to reveal, diagnose, or examine diseases, or medical science, including the study of normal anatomy and physiology. Both classic image processing methods (e.g., denoising, segmentation, deconvolution, registration, feature recognition, and classification) and modern machines, particularly deep learning techniques, represent an indispensable part of bioimaging and related data analysis statistical tools. The trend is on the increase, and we are sure to witness more automation and machine intelligence in the future.

This book emphasizes the latest developments and achievements in Artificial Intelligence (AI) and related technologies with a special focus on Medical Imaging and Diagnostic AI applications. The book describes the theory, applications, and conceptualization of ideas, case studies, and critical surveys covering most aspects of AI for Medical Informatics. The content of this book is divided into three parts: part I presents the role and importance of Machine Learning and Deep Learning Applications in Medical Diagnosis and how these technologies assist in the Smart Prognosis of critical diseases.