Our Students

Students current working with CIVM and recent graduates are listed below.

Austin Kao

Hometown: Hanover Township, NJ

Mentor: G. Allan Johnson

Year: Junior

Major: Electrical & Computer Engineering

Research Focus: Researchers at CIVM have developed methods for quantitative connectomics using tractography derived from MRI. The outpu from a study will typically include maps showing axonal connections (tracts) connecing different parts of the brain. Studies usually include a control group and additonal groups in which there is a genetic or treatment effect. The data is at least 4 dimensional. My project is developpment of an image/display and analysis package that lets CIVM scientists display side by side comparisons of tracts from the control and treated groups, select specific tracts for comparisons, and perform quantitative and visual assessment of differences

Clara Savchik

Hometown: Pittsburgh, PA

Mentor: G. Allan Johnson

Year: Sophomore

Major: Chemistry

Research Focus: My research focuses on developing and testing image alignment techniques to register light sheet data sets to MR images. Testing was first done primarily in ImageJ and Imaris. Now I am focusing my attention on using a registration algorithm within DSI Studio. We hope that the registration can fix some of the distortions innately present in the light sheet data and will be able to analyze the brain in whole new way.

Fernando Zapata

Hometown: Orlando, FL

Mentor: Stephanie Blocker

Year: Junior

Major: Biomedical Engineering

Research Focus: I am developing a web application that will allow researchers and pathologists alike in visualizing tissue data. These visualizations, or "maps," can serve to better characterize the development of cancer and individual tumors within patients. These maps could allow for the possibility of better informed treatment and more objective analysis of patient cases.

Jaclyn Xiao

Hometown: Fremont, California

Mentor: G. Allan Johnson

Year: Sophomore

Major: Biomedical Engineering / Computer Science

Research Focus: Due to the method in which the organism’s brain is prepared and the variability of fluid flow over time, there is concern of whether dMRI images and diffusion tensor parameters are replicable over time. There is also further interest in isolating the time range after active staining in which reproducibility is preserved. The Reproducibility Study is intended to address these questions through statistical analysis on CIVM's dMRI images. Currently, R, Slicer, DSI Studio, and ImageJ are being utilized in this analysis.

Jake Derry

Hometown: Thomson, GA

Mentor: Leonard White

Year: Junior

Major: Computer Science

Research Focus: I’m studying how networks (connectomes) in the brain change following focal stroke in an animal model. While connectome analysis provides an opportunity to explore the complexity of the brain, it comes with the difficulty of discerning truth. In overcoming these obstacles, I hope to see how the brain adapts to an infarction using high resolution dMRI data.

Nick Schiciano

Hometown: Boston, MA

Mentor: G. Allan Johnson

Year: Junior

Major: Biomedical Engineering

Research Focus: My project is development of an atlas of the mouse brain hippocampus. The hippocampus is a central switching hub in the brain. CIVM has acquired the worlds highest resolution connectom data on a mouse brain (more than 1 million times higher than routine human MRI). The brain on which these data were acquired included a genetic marker for projections through the hippocampus. Light sheet microscopy was performed creating a 250GB (big data) image. My project is merging the data from these two (MRI and Light Sheet) extremeley large data sets using several high end display analysis packages and a high performance visualization server.

Orhan Elam

Hometown: New York, NY

Mentor: G. Allan Johnson

Year: Junior

Major: Electrical & Computer Engineering / Biomedical Engineering

Research Focus: My research focuses on ways to represent and contrast histology sections of traditional optical histoplathology images of the mouse brain with the MR histology images acquired at CIVM. I've been working on optimizing the data sets on the Allen Brain Atlas so they can be displayed at their full resolution on regular computers using Slicer software. The end goal is development of code in Slicer to represent a variety of slices at widely varying resolution at once from multiple sources.

Qi Zhao

Hometown: Jinzhou, Liaoning

Mentor: Nian Wang

Year: Graduate Student

Major: Sports Psychology

Research Focus: Diffusion tractography has been successfully used in identifying anatomical connections in human and animal brains. However, most DTI studies in the knee joint and other connective tissues are focused on structural imaging, such as diffusion-weighted imaging and DTI metrics. Application of DTI to map the complex collagen fiber structures in meniscus is still rare, probably because of limited spatial resolution, low fractional anisotropy values, and relatively low SNR. Qi’s project is to investigate the feasibility of tractography of the meniscus at high spatial and angular resolution. It holds the promise to understand the complex collagen fiber connections of the meniscus and its microstructure.

Rees Ridout

Hometown: Searcy, Arkansas

Mentor: Nian Wang

Year: Junior

Major: Biomedical Engineering / Chemistry

Research Focus: Analysis of ACL/PCL and articular knee cartilage with diffusion MRI. Optimization of angular-resolution parameters in order to maximize resolution and minimize scan time. Study of ACL/PCL pathology in opossum knees and resulting diffusional tract data.

Stephanie Crater

Hometown: Chatham, NJ

Mentor: Nian Wang

Year: Junior

Major: Electrical & Computer Engineering / Biomedical Engineering / German

Research Focus: My research is focused on evaluating how the accuracy of generated connectivity matrices changes with changing angular resolution, spatial resolution, and B value. I’m looking at how to best evaluate and compare connectivity matrices and how connectivity changes both between and within different brain regions. I’ll also hopefully be looking at how changing certain tracking parameters can help mitigate the effects of decreased resolution, and what resolution is necessary to generate an acceptably accurate brain connectome.