The field of medical imaging advances so rapidly that all of those working in it, scientists, engineers, physicians, educators and others, need to frequently update their knowledge in order to stay abreast of developments. While journals and periodicals play a crucial role in this, more extensive, integrative publications that connect fundamental principles and new advances in algorithms and techniques to practical applications are essential.

Medical Image Processing: Techniques and Applications meets this challenge and provides an enduring bridge in the ever expanding field of medical imaging. It serves as an authoritative resource and self-study guide explaining sophisticated techniques of quantitative image analysis, with a focus on medical applications. The book emphasizes the conceptual framework of image analysis and the effective use of image processing tools. It presents a detailed approach to each application while emphasizing insight and "tricks of the trade", and the applicability of techniques to other research areas. Although each chapter is written by an expert (or experts) in that area and is essentially self-contained, fundamental connections between the different topics are emphasized so that the book forms an integrated whole.

The book is designed for end users who wish to update their skills and understanding with the latest techniques in image analysis. Providing unprecedented breadth and detail, it will be a valuable cross-disciplinary resource both at the graduate and specialist level. It is also well suited to supplement and motivate learning in graduate-level image processing classes within biomedical engineering, radiology and computer science.

Autorentext
Geoff Dougherty is Professor of Applied Physics and Medical Imaging at California State University Channel Islands, where he teaches both undergraduate and graduate courses in image analysis, pattern recognition and medical imaging. He has been conducting research in the applications of image processing and analysis to medical images for over 20 years. In 2009 he was awarded a Fulbright Senior Scholarship to undertake research in Brisbane, Australia. He has published numerous articles in international journals, and is the author of several book chapters and a textbook in image analysis. He is a Fellow of the IET, a Senior Member of the IEEE and a Member of the American Association of Physicists in Medicine (AAPM), and has held positions at Kuwait University, Keele University, Monash University, the Science University of Malaysia (USM) and the Swiss Federal Institute of Technology (ETH).

Zusammenfassung
The book is designed for end users in the field of digital imaging, who wish to update their skills and understanding with the latest techniques in image analysis. The book emphasizes the conceptual framework of image analysis and the effective use of image processing tools. It uses applications in a variety of fields to demonstrate and consolidate both specific and general concepts, and to build intuition, insight and understanding. Although the chapters are essentially self-contained they reference other chapters to form an integrated whole. Each chapter employs a pedagogical approach to ensure conceptual learning before introducing specific techniques and tricks of the trade. The book concentrates on a number of current research applications, and will present a detailed approach to each while emphasizing the applicability of techniques to other problems. The field of topics is wide, ranging from compressive (non-uniform) sampling in MRI, through automated retinal vessel analysis to 3-D ultrasound imaging and more. The book is amply illustrated with figures and applicable medical images. The reader will learn the techniques which experts in the field are currently employing and testing to solve particular research problems, and how they may be applied to other problems.

Inhalt

Preface.- Contributors.- Introduction.- Rapid Prototyping of Image Analysis Applications.- Seeded Segmentation Methods for Medical Image Analysis.- Deformable Models and Level Sets in Image Segmentation.- Fat Segmentation in Magnetic Resonance Images.- Angiographic Image Analysis.- Detecting and Analyzing Linear Structures in Biomedical Images: A Case Study Using Corneal Nerve Fibers .- Improving and Accelerating the Detection of Linear Features: Selected Applications in Biological Imaging.- Medical Imaging in the Diagnosis of Osteoporosis and Estimation of the Individual Bone Fracture Risk.- Applications of Medical Image Processing in the Diagnosis and Treatment of Spinal Deformity.- Image Analysis of Retinal Images.- Tortuosity as an Indicator of the Severity of Diabetic Retinopathy.- Medical Image Volumetric Visualization: Algorithms, Pipelines and Surgical Applications.- Sparse Sampling in MRI.- Digital Processing of Diffusion-Tensor Images of Avascular Tissues.