Faculty & Staff

I have a joint appointment in Radiology and Neurology and my research has centered on multivariate image based phenotyping, with a focus on neurological conditions like Alzheimer’s disease. I work on imaging and analysis techniques to provide a comprehensive characterization of the brain. MRI is particularly suitable for brain imaging, and diffusion tensor imaging is an important tool for studying brain microstructure, and the connectivity amongst gray matter regions.  Using such techniques, we have developed high resolution, multivariate population atlases for animal models.

I am interested in image segmentation, morphometry and shape analysis, as well as in integrating information from MRI with genetics, and behavior. Our approaches  target: 1) phenotyping the neuroanatomy using imaging; 2) uncovering the link between structural and functional changes, the genetic bases, and environmental factors. I am interested in generating methods and tools for comprehensive phenotyping.
The unique setting of the Center for In Vivo Microscopy (CIVM) provides most imaging modalities for small animals: several MRI systems, micro-CT, SPECT, and multi-photon microscopy, which allow us to integrate imaging data from multiple modalities, and across scales. We use high-performance cluster computing to accelerate our image analysis. We use compressed sensing image reconstruction, and process large image arrays using deformable registration, perform segmentation based on multiple image contrasts including diffusion tensor imaging, as well as voxel based analysis, and graph analysis for connectomics.

At BIAC  my efforts focus on developing multivariate biomarkers and identifying vulnerable networks based on genetic risk for Alzheimer's disease.

My enthusiasm comes from the possibility to extend from single to integrative multivariate and network based analyses to obtain a comprehensive picture of normal development and aging, stages of disease, and the effects of treatments.  I am looking forward to continue working on multivariate image analysis and predictive modeling approaches to help better understand early biomarkers for human disease indirectly through mouse models, as well as directly. The hope is to develop strategies that will help increase the rate at which we grow our current understanding of gray and white matter changes in neurological and psychiatric conditions. 

I am dedicated to supporting an increase in female presence in STEM fields, and love working with students in general. The Bass Connections teams involve undergraduate students in research, while providing them the opportunity to do independent research studies and get involved with the community. These students have for example takes classes such as:

BME 394: Projects in Biomedical Engineering (GE)
BME 493: Projects in Biomedical Engineering (GE)
ECE 899: Special Readings in Electrical Engineering
NEUROSCI 493: Research Independent Study 1