3d Imaging In Medicine

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.

This book provides a quick and systematic presentation of the principles of biomedical visualization and three-dimensional (3D) imaging. Topics discussed include basic principles and algorithms, surgical planning, neurosurgery, orthopedics, prosthesis design, brain imaging, cardio-pulmonary structure analysis and the assessment of clinical efficacy. Students, scientists, researchers, and radiologists will find 3D Imaging in Medicine a valuable source of information for a variety of actual and potential clinical applications for 3-D imaging.

The visualization of human anatomy for diagnostic, therapeutic, and educational pur poses has long been a challenge for scientists and artists. In vivo medical imaging could not be introduced until the discovery of X-rays by Wilhelm Conrad ROntgen in 1895. With the early medical imaging techniques which are still in use today, the three-dimensional reality of the human body can only be visualized in two-dimensional projections or cross-sections. Recently, biomedical engineering and computer science have begun to offer the potential of producing natural three-dimensional views of the human anatomy of living subjects. For a broad application of such technology, many scientific and engineering problems still have to be solved. In order to stimulate progress, the NATO Advanced Research Workshop in Travemiinde, West Germany, from June 25 to 29 was organized. It brought together approximately 50 experts in 3D-medical imaging from allover the world. Among the list of topics image acquisition was addressed first, since its quality decisively influences the quality of the 3D-images. For 3D-image generation - in distinction to 2D imaging - a decision has to be made as to which objects contained in the data set are to be visualized. Therefore special emphasis was laid on methods of object definition. For the final visualization of the segmented objects a large variety of visualization algorithms have been proposed in the past. The meeting assessed these techniques.

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 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.

Comprehensive, yet concise, 3D Printing for the Radiologist presents an overview of three-dimensional printing at the point of care. Focusing on opportunities and challenges in radiology practice, this up-to-date reference covers computer-aided design principles, quality assurance, training, and guidance for integrating 3D printing across radiology subspecialties. Practicing and trainee radiologists, surgeons, researchers, and imaging specialists will find this an indispensable resource for furthering their understanding of the current state and future outlooks for 3D printing in clinical medicine. Covers a wide range of topics, including basic principles of 3D printing, quality assurance, regulatory perspectives, and practical implementation in medical training and practice. Addresses the challenges associated with 3D printing integration in clinical settings, such as reimbursement, regulatory issues, and training. Features concise chapters from a team of multidisciplinary chapter authors, including practicing radiologists, researchers, and engineers. Consolidates today’s available information on this timely topic into a single, convenient, resource.

Digital images have several benefits, such as faster and inexpensive processing cost, easy storage and communication, immediate quality assessment, multiple copying while preserving quality, swift and economical reproduction, and adaptable manipulation. Digital medical images play a vital role in everyday life. Medical imaging is the process of producing visible images of inner structures of the body for scientific and medical study and treatment as well as a view of the function of interior tissues. This process pursues disorder identification and management. Medical imaging in 2D and 3D includes many techniques and operations such as image gaining, storage, presentation, and communication. The 2D and 3D images can be processed in multiple dimensions. Depending on the requirement of a specific problem, one must identify various features of 2D or 3D images while applying suitable algorithms. These image processing techniques began in the 1960s and were used in such fields as space, clinical purposes, the arts, and television image improvement. In the 1970s, with the development of computer systems, the cost of image processing was reduced and processes became faster. In the 2000s, image processing became quicker, inexpensive, and simpler. In the 2020s, image processing has become a more accurate, more efficient, and self-learning technology. This book highlights the framework of the robust and novel methods for medical image processing techniques in 2D and 3D. The chapters explore existing and emerging image challenges and opportunities in the medical field using various medical image processing techniques. The book discusses real-time applications for artificial intelligence and machine learning in medical image processing. The authors also discuss implementation strategies and future research directions for the design and application requirements of these systems. This book will benefit researchers in the medical image processing field as well as those looking to promote the mutual understanding of researchers within different disciplines that incorporate AI and machine learning. FEATURES Highlights the framework of robust and novel methods for medical image processing techniques Discusses implementation strategies and future research directions for the design and application requirements of medical imaging Examines real-time application needs Explores existing and emerging image challenges and opportunities in the medical field