brain

Large Deformation Image Classification Using Generalized Locality-Constrained Linear Coding

Magnetic resonance (MR) imaging has been demonstrated to be very useful for clinical diagnosis of Alzheimer’s disease (AD). A common approach to using MR images for AD detection is to spatially normalize the images by non-rigid image registration, …

Longitudinal Image Registration With Temporally-Dependent Image Similarity Measure

Longitudinal imaging studies are frequently used to investigate temporal changes in brain morphology and often require spatial correspondence between images achieved through image registration. Beside morphological changes, image intensity may also …

Sparse Scale-Space Decomposition of Volume Changes in Deformations Fields

Anatomical changes like brain atrophy or growth are usually not homogeneous in space and across spatial scales, since they map differently depending on the anatomical structures. Thus, the accurate analysis of volume changes from medical images …

Studying Cerebral Vasculature Using Structure Proximity and Graph Kernels

An approach to study population differences in cerebral vasculature is proposed. This is done by 1) extending the concept of encoding cerebral blood vessel networks as spatial graphs and 2) quantifying graph similarity in a kernel-based discriminant …

Large Deformation Diffeomorphic Registration of Diffusion-Weighted Images

Registration of Diffusion-weighted imaging (DWI) data emerges as an important topic in magnetic resonance (MR) image analysis. As existing methods are often designed for specific diffusion models, it is difficult to fit to the registered data …

Longitudinal Image Registration with Non-uniform Appearance Change

Longitudinal imaging studies are frequently used to investigate temporal changes in brain morphology. Image intensity may also change over time, for example when studying brain maturation. However, such intensity changes are not accounted for in …

Metamorphic Geodesic Regression

We propose a metamorphic geodesic regression approach approximating spatial transformations for image time-series while simultaneously accounting for intensity changes. Such changes occur for example in magnetic resonance imaging (MRI) studies of the …

Simple Geodesic Regression for Image Time-Series

Geodesic regression generalizes linear regression to general Riemannian manifolds. Applied to images, it allows for a compact approximation of an image time-series through an initial image and an initial momentum. Geodesic regression requires the …

Temporally-Dependent Image Similarity Measure for Longitudinal Analysis

Current longitudinal image registration methods rely on the assumption that image appearance between time-points remains constant or changes uniformly within intensity classes. This assumption, however, is not valid for magnetic resonance imaging of …

An automated pipeline for cortical surface generation and registration of the cerebral cortex

The human cerebral cortex is one of the most complicated structures in the body. It has a highly convoluted structure with much of the cortical sheet buried in sulci. Based on cytoarchitectural and functional imaging studies, it is possible to …