Visualization in Medicine book cover

Visualization in Medicine

Theory, Algorithms, and Applications

Visualization in Medicine is the first book on visualization and its application to problems in medical diagnosis, education, and treatment. The book describes the algorithms, the applications and their validation (how reliable are the results?), and the clinical evaluation of the applications (are the techniques useful?). It discusses visualization techniques from research literature as well as the compromises required to solve practical clinical problems. The book covers image acquisition, image analysis, and interaction techniques designed to explore and analyze the data. The final chapter shows how visualization is used for planning liver surgery, one of the most demanding surgical disciplines. The book is based on several years of the authors' teaching and research experience. Both authors have initiated and lead a variety of interdisciplinary projects involving computer scientists and medical doctors, primarily radiologists and surgeons.

Audience
Research physicians and scientists in visualization and computer-assisted radiology and surgery; graduate students in visualization and medical imaging; software and algorithm developers in medical imaging companies, such as GE, Siemens Medical Solutions, Philips Medical, Toshiba, and Tiani; developers in visualization companies, such as IBM, Mercury, Vaytec, Kitware, and Silicon Graphics.

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Published: June 2007

Imprint: Morgan Kaufmann

ISBN: 978-0-12-370596-9

Contents

  • Introduction; Chapter 2: Acquisition and Interpretation of Medical Volume Data; Chapter 3: Medical Volume Data in Clinical Practice; Chapter 4: Image Analysis for Medical Visualization; Chapter 5: Exploration of Time Varying Data; Chapter 6: Transfer Function Specification; Chapter 7: Clipping, Cutting and Virtual Resection; Chapter 8: Measurements in Medical Visualization; Chapter 9: Visualization of Anatomic Tree Structures; Chapter 10: Emphasis Techniques in Medical Visualization; Chapter 11: Exploration of MR Diffusion Tensor Images; Chapter 12: Image Analysis and Visualization for Liver Surgery Planning

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