Medical Imaging In Clinical Applications

Covering the basics of X-rays, CT, PET, nuclear medicine, ultrasound, and MRI, this textbook provides senior undergraduate and beginning graduate students with a broad introduction to medical imaging. Over 130 end-of-chapter exercises are included, in addition to solved example problems, which enable students to master the theory as well as providing them with the tools needed to solve more difficult problems. The basic theory, instrumentation and state-of-the-art techniques and applications are covered, bringing students immediately up-to-date with recent developments, such as combined computed tomography/positron emission tomography, multi-slice CT, four-dimensional ultrasound, and parallel imaging MR technology. Clinical examples provide practical applications of physics and engineering knowledge to medicine. Finally, helpful references to specialised texts, recent review articles, and relevant scientific journals are provided at the end of each chapter, making this an ideal textbook for a one-semester course in medical imaging.

This volume comprises of 21 selected chapters, including two overview chapters devoted to abdominal imaging in clinical applications supported computer aided diagnosis approaches as well as different techniques for solving the pectoral muscle extraction problem in the preprocessing part of the CAD systems for detecting breast cancer in its early stage using digital mammograms. The aim of this book is to stimulate further research in medical imaging applications based algorithmic and computer based approaches and utilize them in real-world clinical applications. The book is divided into four parts, Part-I: Clinical Applications of Medical Imaging, Part-II: Classification and clustering, Part-III: Computer Aided Diagnosis (CAD) Tools and Case Studies and Part-IV: Bio-inspiring based Computer Aided diagnosis techniques.

This book presents the first in-depth introduction to parallel imaging techniques and, in particular, to the application of parallel imaging in clinical MRI. It will provide readers with a broader understanding of the fundamental principles of parallel imaging and of the advantages and disadvantages of specific MR protocols in clinical applications in all parts of the body at 1.5 and 3 Tesla.

Medical Imaging in Clinical Practice is a compendium of the various applications of imaging modalities in specific clinical conditions. It captures in an easy to read manner, the experiences of various experts drawn from across the globe. It explores the conventional techniques, advanced modalities and on going research efforts in the ever widening horizon of medical imaging. The various topics would be relevant to residents, radiologists and specialists who order and interpret various medical imaging procedures. It is an essential for the inquisitive mind, seeking to understand the scope of medical imaging in clinical practice.

This new edition is a comprehensive source of imaging informatics fundamentals and how those fundamentals are applied in everyday practice. Imaging Informatics Professionals (IIPs) play a critical role in healthcare, and the scope of the profession has grown far beyond the boundaries of the PACS. A successful IIP must understand the PACS itself and all the software systems networked together in the medical environment. Additionally, an IIP must know the workflows of all the imaging team members, have a base in several medical specialties and be fully capable in the realm of information technology. Practical Imaging Informatics has been reorganized to follow a logical progression from basic background information on IT and clinical image management, through daily operations and troubleshooting, to long-term planning. The book has been fully updated to include the latest technologies and procedures, including artificial intelligence and machine learning. Written by a team of renowned international authors from the Society for Imaging Informatics in Medicine and the European Society of Medical Imaging Informatics, this book is an indispensable reference for the practicing IIP. In addition, it is an ideal guide for those studying for a certification exam, biomedical informaticians, trainees with an interest in informatics, and any professional who needs quick access to the nuts and bolts of imaging informatics.

"An excellent primer on medical imaging for all members of the medical profession . . . including non-radiological specialists. It is technically solid and filled with diagrams and clinical images illustrating important points, but it is also easily readable . . . So many outstanding chapters . . . The book uses little mathematics beyond simple algebra [and] presents complex ideas in very understandable terms." —Melvin E. Clouse, MD, Vice Chairman Emeritus, Department of Radiology, Beth Israel Deaconess Medical Center and Deaconess Professor of Radiology, Harvard Medical School A well-known medical physicist and author, an interventional radiologist, and an emergency room physician with no special training in radiology have collaborated to write, in the language familiar to physicians, an introduction to the technology and clinical applications of medical imaging. It is intentionally brief and not overly detailed, intended to help clinicians with very little free time rapidly gain enough command of the critically important imaging tools of their trade to be able to discuss them confidently with medical and technical colleagues; to explain the general ideas accurately to students, nurses, and technologists; and to describe them effectively to concerned patients and loved ones. Chapter coverage includes: Introduction: Dr. Doe's Headaches Sketches of the Standard Imaging Modalities Image Quality and Dose Creating Subject Contrast in the Primary X-Ray Image Twentieth-Century (Analog) Radiography and Fluoroscopy Radiation Dose and Radiogenic Cancer Risk Twenty-First-Century (Digital) Imaging Digital Planar Imaging Computed Tomography Nuclear Medicine (Including SPECT and PET) Diagnostic Ultrasound (Including Doppler) MRI in One Dimension and with No Relaxation Mapping T1 and T2 Proton Spin Relaxation in 3D Evolving and Experimental Modalities

This book introduces the fundamental aspects of digital imaging and covers four main themes: ultrasound techniques and imaging applications, magnetic resonance and MPJ in hospital, digital imaging with X-rays, and emission tomography (PET and SPECT). Each topic is developed by analyzing the underlying physics principles and their implementation, quality and safety aspects, clinical performance, and recent advancements in the field.

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