Applied Medical Image Processing: A Basic Course

Based on the authors’ decades-long tenure in clinical environments and their extensive teaching experience, Applied Medical Image Processing: A Basic Course introduces the basic methods in applied image processing without assuming that readers have extensive prior knowledge beyond basic applied mathematics, physics, and programming. Illustrated with simple, well-commented MATLAB® examples, the book’s tangible and accessible presentation demonstrates real-life applications. The rapid evolution of radiological imaging in the past four decades has brought medical image processing into the forefront as an essential tool for clinical research, a crucial component of modern diagnostics, and an indispensable element the actual treatment of diseases. A hands-on introduction to the basic image processing algorithms used in clinical routine applications, Applied Medical Image Processing: A Basic Course closes the gap between basic engineering knowledge such as simple programming and applied mathematics on the one hand, and the general understanding of a science that affects the health of a broad public.

Table of Contents:
A Few Basics of Medical Image Sources, J. Hummel Radiology The Electromagnetic Spectrum Basic X-ray Physics Attenuation and Imaging Computed Tomography Magnetic Resonance Tomography Ultrasound Nuclear Medicine and Molecular Imaging Other Imaging Techniques Radiation Protection and Dosimetry Summary and Further References Image Representation, W. Birkfellner Pixels and Voxels Gray Scale and Color Representation Image File Formats DICOM Other Formats – Analyze 7.5, NifTI and Interfile Image Quality and the Signal-to-Noise Ratio Practical Lessons Summary and Further References Operations in Intensity Space, W. Birkfellner The Intensity Transform Function and the Dynamic Range Windowing Histograms and Histogram Operations Dithering and Depth Practical Lessons Summary and Further References Filtering and Transformations, W. Birkfellner The Filtering Operation The Fourier Transform Other Transforms Summary and Further References Segmentation, W. Birkfellner The Segmentation Problem ROI Definition and Centroids Thresholding Region Growing More Sophisticated Segmentation Methods Morphological Operations Evaluation of Segmentation Results Practical Lessons Summary and Further References Spatial Transforms, W. Birkfellner Discretization – Resolution and Artifacts Interpolation and Volume Regularization Translation and Rotation Reformatting Tracking and Image-Guided Therapy Practical lessons Summary and Further References Registration, W. Birkfellner Fusing Information Registration Paradigms Optimization Strategies Some General Comments Camera Calibration Registration to Physical Space Evaluation of Registration Results Practical Lessons Summary and Further References Rendering and Surface Models, W. Birkfellner Visualization Orthogonal and Perspective Projection, and the Viewpoint Raycasting Surface–Based Rendering Practical Lessons Summary and Further References CT Reconstruction, M. Figl Introduction Radon transform Algebraic Reconstruction Some Remarks on Fourier Transform and Filtering Filtered Backprojection Practical Lessons Summary and Further References A Selection of MATLAB Commands Control Structures and Operators I/O and Data Structures Mathematical Functions Further References Glossary Epilogue, W. Birkfellner Index

About the Author :
Wolfgang Birkfellner is head of the Center for Biomedical Engineering and Physics at the Medical University of Vienna.

Review :
[A]n outstanding work that will be of interest to virtually all biomedical engineers. The text is easy to follow, supposing only that the reader has a modest knowledge of linear algebra, basic engineering principles, and computer programming. I was impressed by the content as well as by amount of information that is packed on each page. In each well-organized chapter, important concepts and definitions are described concisely and well. Relevant medical images used for processing compliment many of the concepts discussed. Where important, the mathematical formulation is provided. The text and images refer to several MATLAB-based programming examples that are provided at the end of each chapter. These are useful to apply the concepts to actual medical image processing. The book can be used in part as an excellent reference work for biomedical engineers, scientists, and clinicians. This is a well-written, coherent, and comprehensive work covering the major topics in the field, suitable as a standalone text ! The book is enjoyable to read, and students and professionals will not be bored when doing so. Engineers and scientists will find useful coverage of the field, and students will find the entire volume to be filled with important information. --Edward J. Ciaccio, Columbia University, BioMedical Engineering OnLine, 2011 I have found this book very useful ! . It is comprehensive and well written. --Professor Terry Peters, Robarts Research Institute, The University of Western Ontario This is a lucid, well-written, and hands-on textbook that explains in simple terms and with examples the basic issues of medical image processing. It contains many examples and useful programs. --Professor Leo Joskowicz, Head of Computer-Assisted Surgery and Medical Image Processing Laboratory, The Hebrew University of Jerusalem The plethora of examples in each chapter ! allows the reader to apply the theory and visually assess the outcomes. This book is a perfect blend of theory and practice. I highly recommend it. --Dr. Pascal Fallavollita, Technische Universitat Munchen ! significant and timely. It provides a cogent, not overly simplified, not excessively mathematical treatise of basic principles that the student, trainee, young scientist, and junior practitioner can readily grasp and apply. ! will help facilitate the ongoing, almost magical evolution of modem medical imaging ! they who read this book will be able to make 'a truly useful picture'. --From the Foreword by Richard A. Robb, Ph.D., Mayo Clinic College of Medicine