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"This book presents a comprehensive overview of medical image analysis. Practical in approach, the text is uniquely structured by potential applications. Features : presents learning objectives, exercises and concluding remarks in each chapter, in addition to a glossary of abbreviations; describes a range of common imaging techniques, reconstruction techniques and image artefacts, discusses the archival and transfer of images, including the HL7 and DICOM standards, presents a selection of techniques for the enhancement of contrast and edges, for noise reduction and for edge-preserving smoothing, examines various feature detection and segmentation techniques, together with methods for computing a registration or normalisation transformation, explores object detection, as well as classification based on segment attributes such as shape and appearance, reviews the validation of an analysis method, includes appendices on Markov random field optimization, variational calculus and principal component analysis."

"A text considering the various aspects of the application of image analysis to materials science problems, most especially engineering problems. A guide for applying image analysis to evaluate microstructural features in a variety of materials. Inlcudes bright, detailed color photographs and illustrations, as well as a wealth of black and white images. DLC: Metallography."

"A state-of-the-art review of key topics in medical image perception science and practice, including associated techniques, illustrations and examples. This second edition contains extensive updates and substantial new content. Written by key figures in the field, it covers a wide range of topics including signal detection, image interpretation and advanced image analysis (e.g. deep learning) techniques for interpretive and computational perception. It provides an overview of the key techniques of medical image perception and observer performance research, and includes examples and applications across clinical disciplines including radiology, pathology and oncology. A final chapter discusses the future prospects of medical image perception and assesses upcoming challenges and possibilities, enabling readers to identify new areas for research. Written for both newcomers to the field and experienced researchers and clinicians, this book provides a comprehensive reference for those interested in medical image perception as means to advance knowledge and improve human health."

"This book reviews the algorithms for processing geometric data, with a practical focus on important techniques not covered by traditional courses on computer vision and computer graphics. Features, presents an overview of the underlying mathematical theory, covering vector spaces, metric space, affine spaces, differential geometry, and finite difference methods for derivatives and differential equations, reviews geometry representations, including polygonal meshes, splines, and subdivision surfaces, examines techniques for computing curvature from polygonal meshes, describes algorithms for mesh smoothing, mesh parametrization, and mesh optimization and simplification, discusses point location databases and convex hulls of point sets, investigates the reconstruction of triangle meshes from point clouds, including methods for registration of point clouds and surface reconstruction, provides additional material at a supplementary website, and includes self-study exercises throughout the text."