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.

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.