A picture says more than a thousand words. This is something that we all know to be true. Imaging has been important since the early days of medicine and bi- ogy, as seen in the anatomical studies of Leonardo Da Vinci or Andreas Vesalius. More than 100 years ago, the ?rst noninvasive imaging technologies, such as K- rad Roentgen’s X-ray technology,were applied to the medical ?eld—and while still crude—revolutionized medical diagnosis. Today, every patient will be exposed to some kind of advanced imaging technology such as medical resonance imaging, computed tomography or four-dimensional ultrasound during their lifetime. Many diseases, such as brain tumors, are initially diagnosed solely by imaging, and most of the surgical planning relies on the patient imagery. 4D ultrasound is available to expecting parents who wish to create unique early memories of the new baby, and it may soon be used for the morphometric diagnosis of malformations that may one day be treatable—inutero! Light and electron microscopy are unequal brethren, which have contributed to most of our knowledge about the existence and organization of cells, tissues and microorganisms. Every student of biology or medicine is introduced to the fascinating images of the microcosm. New advances have converted these im- ing technologies, which were considered by many to be antiquated, into powerful tools for research in systems biology and related ?elds.

This book provides an introduction to the role of medical imaging in the diagnosis and management of rheumatologic diseases. It reviews basic radiographic findings of common and rare arthropathies while offering a focused and practical discussion of advanced imaging modalities such as CT, ultrasonography, and MRI. The book begins with a discussion on soft tissue changes, bone and bone density, articular surface changes, and bone alignment. Following this is an examination of the use of advanced imaging modalities including CT, ultrasound, and MRI as well as different disease categories such as inflammatory arthritis, degenerative arthritis, infectious arthritis, and crystalline arthropathy. Subsequent chapters include exercises and case examples for imaging hands and wrists, knees, hips, foot and ankle, shoulder, and the spine. Diagnostic Radiology of Rheumatic Diseases is an essential and practical resource for senior medical students, residents, fellows, and physicians in rheumatology, imaging and radiology, immunology, and internal medicine.

Vorrangig werden radiologische und Ultraschallverfahren vorgestellt. Komplexere Bildgebungsverfahren wie Computertomographie und MRT werden ebenfalls präsentiert. Das Referenzwerk enthält mehr als 1.750 hochwertige Abbildungen und ist eine wahre Fundgrube für Veterinärmediziner, die sich insbesondere auf die Behandlung von Katzen spezialisiert haben. Feline Diagnostic Imaging beschäftigt sich zunächst mit der Auswertung von unauffälligen und pathologischen Röntgenaufnahmen des Thorax, Abdomens und des Bewegungsapparats. Im Anschluss werden Diagnosen aus gängigen echokardiographischen und Ultraschalluntersuchungen erläutert. Auch beschreibt das Referenzwerk bildgebende Untersuchungen des Schädels mittels Computertomographie sowie Gehirn- und Wirbelsäulenerkrankungen, die über ein MRT erkannt werden können. - Präsentiert bildgebende Techniken und konzentriert sich dabei auf die Anforderungen bei der Untersuchung von Katzen. - Legt den Schwerpunkt auf gängige Verfahren, behandelt aber auch komplexere Bildgebungstechniken. - Gibt einen vollständigen Überblick über diagnostischen Imaging-Verfahren bei Katzen. - Mit einer Fülle von Tipps und Tricks für die Behandlung von Katzen. - Ein Muss für Veterinärmediziner, die sich auf Katzen spezialisiert haben. Feline Diagnostic Imaging legt in einzigartiger Weise der Fokus auf Katzen und ist daher ein Muss für Veterinärmediziner, die ihre Kompetenzen bei diagnostischen Bildgebungsverfahren verbessern möchten. Das Buch eignet sich ebenfalls hervorragend für Fachtierärzte für Radiologie, Studenten der Veterinärmedizin und Kliniker.

Imaging technologies are the cornerstone in the diagnosis and staging of benign and malignant lesions in the liver and pancreas. Although the methods are partly competing, they often need to be used in a complementary way in order to obtain optimal results for decision making. The introduction of new and refined non-invasive imaging technologies has lately led to a major progress in the diagnostic approach to diseases of the digestive system. For example, this is the case with echo-enhanced sonography: This technique is based on the property of microbubbles to resonate and emit harmonic waves in an ultrasound field. The initial method, defined as 'second harmonic imaging', was limited by the incapacity to separate the signals obtained from the bubbles and the tissue texture. This procedure has been replaced by the pulse inversion imaging technique which now gives a much better picture quality, allowing to depict the vascularization pattern of distinct lesions in the liver and pancreas. Similarly, the performance of other key imaging modalities such as CT-scan, magnetic resonance imaging, Doppler sonography and endosonography has been improved. Clinicians seeking current information on modern imaging modalities for diagnosis, differentiation and staging of gastrointestinal diseases will find this publication very useful.

Computerized medical imaging and image analysis have been the central focus in diagnostic radiology. They provide revolutionalizing tools for the visualization of physiology as well as the understanding and quantitative measurement of physiological parameters. This book offers in-depth knowledge of medical imaging instrumentation and techniques as well as multidimensional image analysis and classification methods for research, education, and applications in computer-aided diagnostic radiology. Internationally renowned researchers and experts in their respective areas provide detailed descriptions of the basic foundation as well as the most recent developments in medical imaging, thus helping readers to understand theoretical and advanced concepts for important research and clinical applications.

This open access book gives a complete and comprehensive introduction to the fields of medical imaging systems, as designed for a broad range of applications. The authors of the book first explain the foundations of system theory and image processing, before highlighting several modalities in a dedicated chapter. The initial focus is on modalities that are closely related to traditional camera systems such as endoscopy and microscopy. This is followed by more complex image formation processes: magnetic resonance imaging, X-ray projection imaging, computed tomography, X-ray phase-contrast imaging, nuclear imaging, ultrasound, and optical coherence tomography.

Machine Learning and Medical Imaging presents state-of- the-art machine learning methods in medical image analysis. It first summarizes cutting-edge machine learning algorithms in medical imaging, including not only classical probabilistic modeling and learning methods, but also recent breakthroughs in deep learning, sparse representation/coding, and big data hashing. In the second part leading research groups around the world present a wide spectrum of machine learning methods with application to different medical imaging modalities, clinical domains, and organs. The biomedical imaging modalities include ultrasound, magnetic resonance imaging (MRI), computed tomography (CT), histology, and microscopy images. The targeted organs span the lung, liver, brain, and prostate, while there is also a treatment of examining genetic associations. Machine Learning and Medical Imaging is an ideal reference for medical imaging researchers, industry scientists and engineers, advanced undergraduate and graduate students, and clinicians. - Demonstrates the application of cutting-edge machine learning techniques to medical imaging problems - Covers an array of medical imaging applications including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics - Features self-contained chapters with a thorough literature review - Assesses the development of future machine learning techniques and the further application of existing techniques