Research Themes



 brain atlas smBrain Atlas

Construction of population atlases is a key issue in medical image analysis, and particularly in brain mapping. Large sets of images are mapped into a common coordinate system to study intra-population variability and inter-population differences, to provide voxel-wise mapping of functional sites, and help tissue and object segmentation via registration of anatomical labels. A Driving application has been primarily child neuroimaging autism, and recent research focuses on large sets of brain images.

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Research Themes


Research Projects

registration smRegistration

Image registration or alignment is the process of spatially mapping images of different subjects at different time points. We develop novel registration methods for analyzing large population data by using the spatial mappings to determine changes in MR properties and spatial deformations. Our registration methodologies also allow us to develop atlases which describe the likely images and structure that appear in a given population through the computation of diffeomorphisms between subject images and a central image.

diffusion smDiffusion Analysis

Diffusion Tensor Imaging (DTI) has become an important MRI procedure to investigate the integrity of white matter in brain in vivo. DTI is estimated from a series of acquired Diffusion Weighted Imaging (DWI) volumes.This technique, although relatively new, has become increasingly important for studies of anatomical and functional connectivity of the brain regions. DTI is now extensively used to study the fiber architecture in the living human brain It has been shown that brain structures in normal aging undergo significant changes attributed to neurodevelopmental and neurodegeneration processes as a lifelong, dynamic process. Modeling changes in healthy aging is necessary to explain differences to neurodegenerative patterns observed in mental illness and neurological disease. clinical research is often interested in the analysis of whole fiber tracts associated with specific tasks or cognitive function, in neonates as well as in adults.

Age-related changes of tract diffusion properties should therefore be represented at various positions of tracts, informing researchers about anatomical location and type of diffusion changes. We have developed novel methodologies for statistically analyzing DTI datasets among population groups.

segmentation smSegmentation

Segmentation is typically the first step in extracting useful information from medical images, where we determine the underlying anatomy. Tissue segmentation, which partitions brain magnetic resonance (MR) images into gray matter (GM), white matter (WM), and erebrospinal fluid (CSF), is a crucial step for subsequent volumetric and cortical surface analysis. effective segmentation of neonatal brain images still remains a great challenge in many emerging neonatal studies, which have the potential of revealing interesting brain developmental patterns and also neurodevelopmental disorders.We develop segmentation schemes for healthy adults, neonatal (newborn) infants, and adults.

longitudinal smLongitudinal Analysis

Analysis of human brain development is a crucial step for improved understanding of neurodevelopmental disorders. We focus on brain development as observed in neonates and children, characterizing brain development through analysis of contrast changes in MRI and DTI of children undergoing healthy brain development as well as in children at risk of neurological disorders. We discuss spatio-temporal brain development using voxel-based, atlas-based ROI, and data driven analyses to gain a better understanding at this crucial developmental stage.

shape analysis smShape Analysis

The anatomical structures of interest that we study within the brain are complex and need to be characterized in a consistent, reliable manner. We at UCNIA are developing methods for representing and analyzing shapes from image data to facilitate the study of anatomical changes. This also includes the development of shape alignment procedures, spatial correspondence estimation, and statistical analysis of shape parameters.

The purpose is to characterize the neuroanatomical variations observed in neurological disorders such as dementia. We do global statistical analysis of brain anatomy and identify relevant shape deformation patterns that explain corresponding variations in clinical neuropsychological measures. The motivation is to model the inherent relation between anatomical shape and clinical measures and evaluate its statistical significance.

One of the primary goals of computational anatomy is the statistical analysis of anatomical variability in large populations of images.

microscopy smMicroscopy

Electron microscopy is an unique modality for scientists attempting to map the anatomy of individual neurons and their connectivity because it has a resolution that is high enough to identify synaptic contacts and gap junctions. These are important indicators for types of neuron topology and are required for neural circuit reconstruction.

Neural network reconstruction or connectomics is the complete mapping of all individual neurons in a region, including their synaptic contacts, to create its canonical network map, also known as a connectome.

simulation smSimulation

Numerical simulation has matured into a vital tool for scientific and medical research. Cheaper and safer than physical experiments, simulation allows us to tighten the loop between clinical insight, theoretical development, and model validation.