Computational neuroanatomy is an emerging field that utilizes various non-invasive brain imaging modalities, such as MRI and DTI, in quantifying the spatiotemporal dynamics of the human brain structures in both normal and clinical populations. This discipline emerged about twenty years ago and has made substantial progress in the past decade. The main goals of this book are to provide an overview of various mathematical, statistical and computational methodologies used in the field to a wide range of researchers and students, and to address important yet technically challenging topics in further detail.
Contents:Statistical PreliminaryDeformation-Based MorphometryTensor-Based MorphometryVoxel-Based MorphometryGeometry of Cortical ManifoldsSmoothing on Cortical ManifoldsSurface-Based MorphometryWeighted Fourier RepresentationStructural Brain ConnectivityTopological Data Analysis
Readership: Researchers and graduate students in the fields of computational neuroscience and brain imaging, medical image analysis and pattern recognition.