Visualization and Processing of Tensor Fields [Paperback]

Matrix-valued data sets  so-called second order tensor fields  have gained significant importance in scientific visualization and image processing due to recent developments such as diffusion tensor imaging. This book is the first edited volume that presents the state of the art in the visualization and processing of tensor fields. It contains some longer chapters dedicated to surveys and tutorials of specific topics, as well as a great deal of original work by leading experts that has not been published before. It serves as an overview for the inquiring scientist, as a basic foundation for developers and practitioners, and as as a textbook for specialized classes and seminars for graduate and doctoral students.Matrix-valued data sets  so-called second order tensor fields  have gained significant importance in scientific visualization and image processing due to recent developments such as diffusion tensor imaging. This book is the first edited volume that presents the state of the art in the visualization and processing of tensor fields. It contains some longer chapters dedicated to surveys and tutorials of specific topics, as well as a great deal of original work by leading experts that has not been published before. It serves as an overview for the inquiring scientist, as a basic foundation for developers and practitioners, and as as a textbook for specialized classes and seminars for graduate and doctoral students.An Introduction to Tensors.- Feature Detection with Tensors.- Adaptive Structure Tensors and their Applications.- On the Concept of a Local Greyvalue Distribution and the Adaptive Estimation of a Structure Tensor.- Low-level Feature Detection Using the Boundary Tensor.- Diffusion Tensor Imaging.- An Introduction to Computational Diffusion MRI: the Diffusion Tensor and Beyond.- Random Noise in Diffusion Tensor Imaging, its Destructive Impact and Some Corrections.- An Introduction to Visualization of Diffusion Tensor Imaging and Its Applications.- Anl³$