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Visualization in Industrial X-Ray Computed Tomography
Hardcover
Series: Mathematics and Visualization
Technology & EngineeringGeneral ComputersGeneral Mathematics
PREORDER - Expected ship date February 24, 2027
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ISBN10: 3032325005
ISBN13: 9783032325006
Publisher: Springer
Published: Feb 24 2027
Pages: 640
Language: English
ISBN13: 9783032325006
Publisher: Springer
Published: Feb 24 2027
Pages: 640
Language: English
This book is the first one to focus on the intersection of visualization and X-ray computed tomography (XCT). While XCT, as a non-destructive imaging technique, generates detailed information about structures and characteristics of the specimens, proper visualization of the resulting data facilitates novel and previously impossible insights and yields an in-depth understanding of complex phenomena at multiple scales, in different dimensions, or different modalities. Major challenges emerge from the huge variety of scanned objects and dataset sizes that almost routinely reach the terabyte range; all this asks for a careful rethinking of methods on data handling and visualization.
Concepted at the intersection of the two almost disjoint domains of visualization and industrial XCT, this book compiles the state of the art and integrates some of the latest advancements from mathematical concepts to visual metaphors as well as respective algorithms and data structures. It discusses current applications and upcoming research streams in different stages of the visualization pipeline. The book is structured into three main parts. Fundamental Concepts: Fundamental definitions, concepts, and theory of X-ray imaging including different XCT modalities are addressed together with the foundations of data handling. Finally, the notion of Rich XCT data is introduced as a conceptional basis for the visualization tasks to follow. The Visualization Pipeline: Besides standard visualization tasks like rendering, more advanced concepts such as multivariate data analysis, visual analysis of high dimensional data, imaging and tracking of dynamic phenomena, topology-driven approaches, and immersive analytics are discussed. Further contributions consider the visualization of quantitative data as well as uncertainty quantification and visualization. In addition, fundamental aspects of data processing, from reconstruction of XCT data, global and local (de-)compression to segmentation of relevant features are treated in detail. Applications: Industrial applications in outstanding case studies of XCT visualization are presented, covering quantitative 3D to 4D materials science for aeronautic applications and quantification of tomographic images of fiber-reinforced composites.
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