Longitudinal Registration with Group-Wise Similarity Prior
, the LDDMM energy functional is defined as: (1)where is a time dependent velocity field drawn from the reproducing kernel Hilbert space (RKHS) V. The RKHS is specified by the…
the Brain Surface from CT Images with Artifacts Using Dictionary Learning for Non-rigid MR-CT Registration
Fig. 1. Dictionary-based appearance learning and segmentation of post-surgical cortical brain surface in CT images for direct non-rigid registration of with pre-surgical MRI. We use a training set of post-implantation…
Transfer: Spectral Analysis of Cortical Surfaces and Functional Maps
Fig. 1. Spectral Decomposition on Shapes – Any function f(x) on surface 1 (top row), or g(x) on surface 2 (bottom row) can be written as a sum of weighted…
Robust Probabilistic Model for Motion Layer Separation in X-ray Fluoroscopy
compared to the state of the art. In addition, we show qualitative improvements on real X-ray data. 1 Introduction Minimally-invasive interventions are often guided by fluoroscopic X-ray imaging. X-ray imaging…
Tumor Growth Prediction with Multiplicative Growth and Image-Derived Motion
3.5 %, 85.6 7.5 %, 87.4 3.6 %, 9.7 7.2 %, and 0.6 0.2 mm, respectively. The rights of this work are transferred to the extent transferable according to title 17 U.S.C. 105. 1 Introduction Pancreatic neuroendocrine tumors are…
Trajectory and Progression Score Estimation from Voxelwise Longitudinal Imaging Measures: Application to Amyloid Imaging
-amyloid deposition begins in Alzheimer’s disease (AD) years before the onset of any clinical symptoms. It is therefore important to determine the temporal trajectories of amyloid deposition in these earliest stages…
Diffeomorphic Mapping for Cortical Surfaces
, such that is a function at resolution r, , with the level of detail increasing as r increases. Let be a triangular surface mesh, where is a set of…
Nonlinear Mixed Effects Models for Longitudinal Image Data
, are usually observed and/or normalized in a large number of locations of a common space, denoted by , across multiple time points . Also, is often a compact subset…
Compressed-Sensing Approach for Super-Resolution Reconstruction of Diffusion MRI
to which is too large to study certain brain structures that are a few millimeters thick. Due to signal loss from decay with longer echo times, reducing the voxel size…
Unifying Framework for Spatial and Temporal Diffusion in Diffusion MRI
with the real displacement vector and the diffusion time. In DW-MRI the EAP is estimated by obtaining diffusion-weighted images (DWIs). A DWI is obtained by applying two sensitizing diffusion gradients…
