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This book offers concise descriptions of cross-sectional imaging studies of the abdomen and pelvis, supplemented with over 1100 high-quality images and discussion of state-of-the-art techniques. It is based on the most common clinical cases encountered in daily practice and uses an algorithmic approach to help radiologists arrive first at a working differential diagnosis and then reach an accurate diagnosis based on imaging features, which incorporate clinical, laboratory, and other underlying contexts. The book is organized by anatomical organ of origin and each chapter provides a brief anatomical background of the organ under review; explores various cross-sectional imaging techniques and common pathologies; and presents practical algorithms based on frequently encountered imaging features. Special emphasis is placed on the role of computed tomography (CT) and magnetic resonance imaging (MRI). In addition to algorithmic coverage of many pathological entities in various abdominopelvic organs, unique topics are also examined, such as imaging of organ transplant (including kidney, liver and pancreas), evaluation of perianal fistula, and assessment of rectal carcinoma and prostate carcinoma by MRI. Cross-Sectional Imaging of the Abdomen and Pelvis: A Practical Algorithmic Approach is a unique and practical resource for radiologists, fellows, and residents.
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"Neuroscience is, by definition, a multidisciplinary field: some scientists study genes and proteins at the molecular level while others study neural circuitry using electrophysiology and high-resolution optics. A single topic can be studied using techniques from genetics, imaging, biochemistry, or electrophysiology. Therefore, it can be daunting for young scientists or anyone new to neuroscience to learn how to read the primary literature and develop their own experiments. This volume addresses that gap, gathering multidisciplinary knowledge and providing tools for understanding the neuroscience techniques that are essential to the field, and allowing the reader to design experiments in a variety of neuroscience disciplines"--Publisher's description.
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