3D Imaging, Analysis and Applications brings together core topics, both in terms of well-established fundamental techniques and the most promising recent techniques in the exciting field of 3D imaging and analysis. Many similar techniques are being used in a variety of subject areas and applications and the authors attempt to unify a range of related ideas. With contributions from high profile researchers and practitioners, the material presented is informative and authoritative and represents mainstream work and opinions within the community. Composed of three sections, the first examines 3D imaging and shape representation, the second, 3D shape analysis and processing, and the last section covers 3D imaging applications. Although 3D Imaging, Analysis and Applications is primarily a graduate text, aimed at masters-level and doctoral-level research students, much material is accessible to final-year undergraduate students. It will also serve as a reference text for professional academics, people working in commercial research and development labs and industrial practitioners.

This textbook is designed for postgraduate studies in the field of 3D Computer Vision. It also provides a useful reference for industrial practitioners; for example, in the areas of 3D data capture, computer-aided geometric modelling and industrial quality assurance. This second edition is a significant upgrade of existing topics with novel findings. Additionally, it has new material covering consumer-grade RGB-D cameras, 3D morphable models, deep learning on 3D datasets, as well as new applications in the 3D digitization of cultural heritage and the 3D phenotyping of crops. Overall, the book covers three main areas: ● 3D imaging, including passive 3D imaging, active triangulation 3D imaging, active time-of-flight 3D imaging, consumer RGB-D cameras, and 3D data representation and visualisation; ● 3D shape analysis, including local descriptors, registration, matching, 3D morphable models, and deep learning on 3D datasets; and ● 3D applications, including 3D face recognition, cultural heritage and 3D phenotyping of plants. 3D computer vision is a rapidly advancing area in computer science. There are many real-world applications that demand high-performance 3D imaging and analysis and, as a result, many new techniques and commercial products have been developed. However, many challenges remain on how to analyse the captured data in a way that is sufficiently fast, robust and accurate for the application. Such challenges include metrology, semantic segmentation, classification and recognition. Thus, 3D imaging, analysis and their applications remain a highly-active research field that will continue to attract intensive attention from the research community with the ultimate goal of fully automating the 3D data capture, analysis and inference pipeline.

Over the last decade, significant progress has been made in 3D imaging research. As a result, 3D imaging methods and techniques are being employed for various applications, including 3D television, intelligent robotics, medical imaging, and stereovision. Depth Map and 3D Imaging Applications: Algorithms and Technologies present various 3D algorithms developed in the recent years and to investigate the application of 3D methods in various domains. Containing five sections, this book offers perspectives on 3D imaging algorithms, 3D shape recovery, stereoscopic vision and autostereoscopic vision, 3D vision for robotic applications, and 3D imaging applications. This book is an important resource for professionals, scientists, researchers, academics, and software engineers in image/video processing and computer vision.

The ability to visualize, non-invasively, human internal organs in their true from and shape has intrigued mankind for centuries. While the recent inventions of medical imaging modalities such as computerized tomography and magnetic resonance imaging have revolutionized radiology, the development of three-dimensional (3D) imaging has brought us closer to the age-old quest of non-invasive visualization. The ability to not only visualize but to manipulate and analyze 3D structures from captured multidimensional image data, is vital to a number of diagnostic and therapeutic applications. 3D Imaging in Medicine, Second Edition, unique in its contents, covers both the technical aspects and the actual medical applications of the process in a single source. The value of this technology is obvious. For example, three dimensional imaging allows a radiologist to accurately target the positioning and dosage of chemotherapy as well as to make more accurate diagnoses by showing more pathology; it allows the vascular surgeon to study the flow of blood through clogged arteries; it allows the orthopedist to find all the pieces of a compound fracture; and, it allows oncologists to perform less invasive biopsies. In fact, one of the most important uses of 3D Imaging is in computer-assisted surgery. For example, in cancer surgery, computer images show the surgeon the extent of the tumor so that only the diseased tissue is removed. In short, 3D imaging provides clinicians with information that saves time and money. 3D Imaging in Medicine, Second Edition provides a ready reference on the fundamental science of 3D imaging and its medical applications. The chapters have been written by experts in the field, and the technical aspects are covered in a tutorial fashion, describing the basic principles and algorithms in an easily understandable way. The application areas covered include: surgical planning, neuro-surgery, orthopedics, prosthesis design, brain imaging, analysis of cardio-pulmonary structures, and the assessment of clinical efficacy. The book is designed to provide a quick and systematic understanding of the principles of biomedical visualization to students, scientists and researchers, and to act as a source of information to medical practitioners on a wide variety of clinical applications of 3D imaging.

Few fields have witnessed such impressive advances as the application of computer technology to radiology. The progress achieved has revolutionized diagnosis and greatly facilitated treatment selection and accurate planning of procedures. This book, written by leading experts from many different countries, provides a comprehensive and up-to-date overview of the role of 3D image processing. The first section covers a wide range of technical aspects in an informative way. This is followed by the main section, in which the principal clinical applications are described and discussed in depth. To complete the picture, the final section focuses on recent developments in functional imaging and computer-aided surgery. This book will prove invaluable to all who have an interest in this complex but vitally important field.

Electron microscope tomography (EMT) has emerged as the leading technique for three-dimensional (3D) structural analysis of unique complex biological specimens. This book reviews the different computational stages involved in EMT, from image acquisition to interpretation of the 3D reconstruction. The high performance computing (HPC) techniques normally used to cope with the computational demands are also described. Moreover, combining the holographic methods with the methods for digital image processing has made it possible to develop the digital holographic interference microscope (DHIM) for real-time 3D imaging of phase microscopic objects and measurement of their morphological parameters. In this book, the classical and holographic methods of phase microobject visualisation are considered. In addition, 3D imaging has become commonplace in the medical field, with its routine use in the better established institutions for pre-natal observations, diagnosis of ailments, work-up prior to surgery, recovery monitoring and many other medical procedures. This book discusses the research methodology required in the reconstruction of 3D volume and employing computer-aided diagnosis to identify various diseases. Details of the different stages of processing, along with the promising results achieved are presented. Also discussed are some considerations for future trends of 3D imaging in the medical field. Other chapters cover detailed derivations of reconstruction algorithms in 2D and modern 3D cone-beam CT (CBCT), evaluate geometric parameters of bone in 3D using CT scans or a new low-radiating device (EOS), and CT based 3D- display providing accurate preoperative visualisation and computerised risk analyses for safety margins of pancreatic- and biliary- tract tumours, as well as for the assessment of abdominal aortic aneurysms (AAA).

This book presents cutting-edge research and applications of deep learning in a broad range of medical imaging scenarios, such as computer-aided diagnosis, image segmentation, tissue recognition and classification, and other areas of medical and healthcare problems. Each of its chapters covers a topic in depth, ranging from medical image synthesis and techniques for muskuloskeletal analysis to diagnostic tools for breast lesions on digital mammograms and glaucoma on retinal fundus images. It also provides an overview of deep learning in medical image analysis and highlights issues and challenges encountered by researchers and clinicians, surveying and discussing practical approaches in general and in the context of specific problems. Academics, clinical and industry researchers, as well as young researchers and graduate students in medical imaging, computer-aided-diagnosis, biomedical engineering and computer vision will find this book a great reference and very useful learning resource.