Aly A. FaragCambridge University Press, 10/30/2014EAN 9780521196796, ISBN10: 0521196795Hardcover, 496 pages, 24.7 x 17.4 x 2.7 cmLanguage: EnglishIdeal for classroom use and self-study, this book explains the implementation of the most effective modern methods in image analysis, covering segmentation, registration and visualisation, and focusing on the key theories, algorithms and applications that have emerged from recent progress in computer vision, imaging and computational biomedical science. Structured around five core building blocks - signals, systems, image formation and modality; stochastic models; computational geometry; level set methods; and tools and CAD models - it provides a solid overview of the field. Mathematical and statistical topics are presented in a straightforward manner, enabling the reader to gain a deep understanding of the subject without becoming entangled in mathematical complexities. Theory is connected to practical examples in x-ray, ultrasound, nuclear medicine, MRI and CT imaging, removing the abstract nature of the models and assisting reader understanding.1. Overview of biomedical image analysisPart I. Signals and Systems, Image Formation, and Image Modality2. Overview of two-dimensional signals and systems3. Biomedical imaging modalitiesPart II. Stochastic Models4. Random variables5. Random processes6. Basics of random fields7. Probability density estimation by linear modelsPart III. Computational Geometry8. Basics of topology and computational geometry9. Geometric features extractionPart IV. Variational Calculus and Level Set Methods10. Variational approaches and level setsPart V. Image Analysis Tools11. Segmentation – statistical approach12. Segmentation – variational approach13. Basics of registration14. Variational methods for shape registrations15. Statistical models of shape and appearance.
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