Advanced Topics on Three-Dimensional Ultrasound in Obstetrics and Gynecology is a comprehensive and handy guide for sonographers, obstetricians, gynecology and radiology professionals, and all technicians working in ultrasound laboratories who are interested in taking advantage of all the resources provided by this imaging technique. The book is divided in three sections which give information on a variety of relevant topics: • Three-Dimensional Ultrasound Instrumentation and Technology. This section explains different ultrasound methods that can be used for three-dimensional imaging. It is complemented by a discussion on how to use the techniques in telemedicine. • The Use of Three-Dimensional Ultrasound During Pregnancy. This section explains the methods used to assess fetal organs, behavior and defects during different stages of pregnancy. • ‎The Use of Three-Dimensional Ultrasound When Evaluating Female Reproductive Physiology. This section covers diagnostic procedures for ovarian and uterine abnormalities and neoplasms.

Current and Future Application of Artificial Intelligence in Clinical Medicine presents updates on the application of machine learning and deep learning techniques in medical procedures. . Chapters in the volume have been written by outstanding contributors from cancer and computer science institutes with the goal of providing updated knowledge to the reader. Topics covered in the book include 1) Artificial Intelligence (AI) applications in cancer diagnosis and therapy, 2) Updates in AI applications in the medical industry, 3) the use of AI in studying the COVID-19 pandemic in China, 4) AI applications in clinical oncology (including AI-based mining for pulmonary nodules and the use of AI in understanding specific carcinomas), 5) AI in medical imaging. Each chapter presents information on related sub topics in a reader friendly format. </p> The combination of expert knowledge and multidisciplinary approaches highlighted in the book make it a valuable source of information for physicians and clinical researchers active in the field of cancer diagnosis and treatment (oncologists, oncologic surgeons, radiation oncologists, nuclear medicine physicians, and radiologists) and computer science scholars seeking to understand medical applications of artificial intelligence.

Medical Imaging Technologies and Methods for Health Care provides timely, evidence-based information that helps readers understand innovations in medical imaging. These innovations are computer / imaging based technologies which are set to have a bigger impact on the detection and management of human diseases. This volume covers: -Image processing and analyses -Computer-aided diagnosis and detection -Data mining in medical imaging -Mobile picture archiving and communications systems (PACS) -Image analytic methods in bone mineral density and detection of Alzheimer’s disease -Biomedical engineering methods applied in biomedical imaging This volume is intended as a useful resource for undergraduate and post-graduate students in medical imaging technology, radiographers, doctors, biomedical engineers, researchers and practitioners in health care.

With the success in the surgical treatment of congenital heart disease, the population of adults with congenital heart disease requiring imaging is soaring. The Role of Imaging in Adults with Congenital Heart Disease: A State-of-the-Art Review is a practical reference guide that covers each major category of congenital heart disease, providing an overview of the diseases as well as specific imaging recommendations for each disease. This Ebook has been written for cardiologists who encounter adults with congenital heart disease in clinical practice as an aid to help these patients with appropriate imaging. Additionally, the Ebook includes numerous color illustrations of the imaging modalities used, as well as a full appendix of additional images. It also includes a summary of the 2008 ACC/AHA Guidelines for Management of Adults with Congenital Heart Disease as a second appendix. It is considered essential reading for practitioners in this field.

How to Optimally Sample and Resample Images: Theory and Methods Using MATLAB provides updated formulations of image sampling theory and practical algorithms of image sampling with sampling rates close to the theoretical minimum, and also introduces interpolation error-free methods of image resampling. Readers will be informed about relevant principles and applications of image sampling with the help of MATLAB©. The information presented in the book, across 9 chapters, will help readers to understand processes that make analog to digital signal conversion efficient for modern imaging devices. Key Features: - Introduces readers to classical sampling theorems - Presents updated information about image sampling and resampling formulations with reference to theoretical minimums - Presents information on practical and fast sampling algorithms - Presents information about interpolation error-free methods of image resampling - Presents examples of applications of the described methods - Is supplemented by a MATLAB© program package for exercising knowledge. The book is a suitable handbook for engineers and technicians involved in imaging engineering and related applications as well as engineering students learning about digital signal processing techniques.

This eBook is a collection of comprehensive and cutting edge book articles written by leading experts on digital signal and image processing in general, and specifically book written by one of pioneers of digital holography, one of the foremost branches of the image sciences and modern information technology. It covers all the basic aspects of digital synthesis and numerical reconstruction of holograms, beginning from digital holographic transforms, going on to fast numerical algorithms for reconstruction of digitally recorded holograms, and then to computer generated holograms and their applications in hybrid digital-optical image processing and 3D visualization and communication. It also offers a comprehensive review of image digital processing methods most relevant to digital holography. The volume appears at an appropriate time, i.e. while the field of optics is mutating from micro to nano and advanced optical technologies are becoming digital. It is written for researchers and advanced graduate and PhD students in the field of optics, photonics, electrical engineering, and biomedical engineering and related branches of experimental physics and natural sciences and should prove to be of great value to them. It can also be used as a text book for one-semester course.

Intelligent Diagnosis of Lung Cancer and Respiratory Diseases presents information about diseases of the respiratory system and the relevant diagnostic imaging techniques. The book focuses on intelligent diagnostic imaging systems. The first section of the book deals with the physiological underpinnings of 3 major diseases that affect the respiratory system: tuberculosis, lung cancer and COVID-19. This section also explains the basic principles of artificial Intelligence that support the diagnosis of these diseases. The next section presents applications of intelligent systems to support the imaging diagnosis of COVID-19 and lung cancer, with emphasis on digital health and telemedicine approaches. Each chapter is organized into a readable format, and is accompanied with a detailed bibliographical information for further reading. This book is a reference for everyone seeking to understand how artificial intelligence can provide solutions for diagnostic support systems by processing and analyzing radiological images to improve early diagnosis and, consequently, lung disease prognosis.

This ebook covers fast transform algorithms, analyses, and applications in a single volume. It is the result of the collaboration by the author with others in the world wide university community and has been accumulated over the author&amp;amp;rsquo;s working lifetime of about 40 years. It has now culminated in a nice mix of theoretical development and practical uses of various fast transforms. Thus readers will find practical approaches not covered elsewhere for the design and development of fast transform methods. Some of the most immediate applications, such as detection and analysis of periodicities in data, signal denoising and deblurring, signal resampling, precise differentiation and integration are covered and supported by concrete algorithms in this book. Other potential applications are supported by a tour of the theory and mathematical abstraction. The book is addressed to a broad circle of experimentalists, researchers and students that are not regularly educated in signal processing and work in various fields in experimental sciences ranging from physics a to metrology and to biomedical engineering.