Digital Image Processing for Medical Applications is a practical text for a first course in image processing and analysis for final-year undergraduates or first-year graduate students. Designed for readers who will become 'end users' of digital image processing in the biomedical sciences, it emphasizes the conceptual framework and the effective use of image processing tools, not the underlying mathematical theory or computer programming.
Image processing is a hands-on discipline, and the best way to learn is by doing. This book takes its motivation from medical applications and uses real medical images and situations to clarify and consolidate concepts and to build intuition, insight and understanding. Concepts, techniques and algorithms are introduced, then illustrated through examples, then applied by the students themselves to typical medical imaging problems. The book avoids the advanced mathematical development of other textbooks, using mathematics as a tool and only when necessary.
Careful discussions of the major medical imaging modalities enable students to understand the diagnostic tasks for which images are needed and the typical distortions and artifacts associated with each modality. This knowledge then motivates the presentation of the techniques needed to reverse distortions, minimize artifacts and enhance important features. Students understand why they are undertaking particular operations, and the practical activities enable them to see in real time how operations affect real images. Theory and practice are linked, each reinforcing the other.
Chapter features for students
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Overviews summarize the essential purpose of the material covered in the chapter.
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Learning objectives list the specific knowledge and skills to be acquired.
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Hands-on activities build intuition, skills and confidence.
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End-of-chapter exercises reinforce understanding.