Lie Algebras for Fast Diffeomorphic Image Registration
. An image will be a square-integrable function on , that is, an element of . Let denote the Lie group of smooth diffeomorphisms on . The Lie algebra for…
Mixed-Effects Model with Time Reparametrization for Longitudinal Univariate Manifold-Valued Data
() peptide, increasing CSF tau protein and neurodegeneration, characterized by cerebral atrophy and neuron loss. In order to increase the chances of success of a given treatment, the need for…
of Longitudinal Development of Infant Cortical Surface Shape Using a 4D Current-Based Learning Framework
with high accuracy as demonstrated in [11]. More details can be found in [10, 11]. Cortical Surface Representation Using Currents. The concept of representing a surface as a current derives…
Biomarker Models for Progression Estimation in Alzheimer’s Disease
indicating the disease progress of a subject by fitting its ADAS scores to this curve. Similarly, Delor et al. [2] compute a disease onset time by adjusting subjects according to…
Optimal Transport Averaging of Neuroimaging Data
. Simply put, we consider normalized histograms on a grid of locations, and assume the distance between any two locations is provided. Next, we extend Wasserstein distances to non-negative vectors…
Testing for Longitudinal Data
Fig. 1. A toy example in Euclidean space. Top: (a) Cross-sectional data of two groups, illustrated as red circles and blue squares; (b) the same data with longitudinal information (middle)…
High Spatial Resolution Diffusion-Weighted Imaging
22 mm to 111 mm requires 128 times more imaging time at equal SNR; a 5 min. acquisition would thus become a 10.7 h. acquisition, which is not realistic. Enhancing the spatial resolution requires…
Segmentation and Registration Through the Duality of Congealing and Maximum Likelihood Estimate
Fig. 1. Microscope images of Drosophila melanogaster imaginal discs with gene expression patterns (Color figure online). A popular method which aligns images and simultaneously estimates a simple statistical shape model…
Multimodal Joint Generative Model of Brain Data
given an observed image from a different imaging modality and a database of N previously observed image pairs , indexed by n. Note that the technique can be easily extended…
from Determinantal Point Processes for Scalable Manifold Learning
for n points. Since this algorithm has the same complexity as the spectral analysis, it cannot be directly used as a subset selection scheme. In this paper, we focus on…
