Medical Image Analysis presents practical knowledge on medical image computing and analysis as written by top educators and experts. This text is a modern, practical, self-contained reference that conveys a mix of fundamental methodological concepts within different medical domains. Sections cover core representations and properties of digital images and image enhancement techniques, advanced image computing methods (including segmentation, registration, motion and shape analysis), machine learning, how medical image computing (MIC) is used in clinical and medical research, and how to identify alternative strategies and employ software tools to solve typical problems in MIC.
– An authoritative presentation of key concepts and methods from experts in the field
– Sections clearly explaining key methodological principles within relevant medical applications
– Self-contained chapters enable the text to be used on courses with differing structures
– A representative selection of modern topics and techniques in medical image computing
– Focus on medical image computing as an enabling technology to tackle unmet clinical needs
– Presentation of traditional and machine learning approaches to medical image computing