Provost Undergraduate Research Award

Under supervision of Dr. J T Ratnanather, I was awarded a PURA award for Summer 2010 to work on a project entitled "A New Approach to Biomedical Ontologies." More information about this specific project can be found lower on the page.

According to the website (which has much more information about the selection process):

The PURA program affords Johns Hopkins University students unique opportunities to conduct undergraduate research. Founded in 1993 on the belief that encouraging undergraduates to engage in research activity enhances the learning experience and helps to develop investigative skills, the PURA program is an important part of the university’s mission.

These awards are of a variable amount; my project was awarded the maximum of $2,500.

CER Technology Fellowship (2)

The Center for Educational Resources annually grants technology fellowships

designed to help Hopkins faculty develop digital course resources by combining their instructional expertise and project design capabilities with the technology skills of students who are interested inenhancing their digital portfolios. The focus of this program is to create instructional resources that support undergraduate education.

With professor Tilak Ratnanather, I have been awarded two of these fellowships to develop an Interactive Introduction to Metric Pattern Theory.  More details in the "Research" section below.

Each fellowship is worth $4,000 for the student and $1,000 for the professor.

Ontological Labels in Cardiovascular Atlases

Computational Anatomy methods make it possible to locate differences in anatomical structures in disease. As an example, significant tissue expansion in the mood anterior regions of the left ventricular (LV) myocardium et end systole (ES) of the cardiac cycle was observed in patients with myocardial infarction and nonischemic cardiomyopathy (Ardekani et al., 2009; doi:10.007/s10439-009-9677-2). Using an LV atlas with ontological labels, it is possible to automate the identification of statistically significant regions.

We were then able to query the application ontology to find which regions showed the highest average and most significant tissue volume expansion. Our findings both agree with the human assessment of the location and provide finer granularity (e.g. allowing us to calculate the average expansion by voxel for each region of myocardium).

Ontologies are increasingly proving a powerful tool for data annotation ( Turner et. al, doi: 10.3389/fninf.2010.00010 for example). While computational anatomy has been established as a powerful tool for diagnosing disease and disorder, the addition of ontological annotation provides smarter, computer-processable information on top of Large Deformation Diffeomorphic Metric Mapping (LDDMM) metadata.

In principle, the tools used in this paper will quickly and automatically register images to an appropriate atlas and locate regions of interest, affirming or providing the diagnosis of a clinician. Furthermore, the information stored in the Foundational Model of Anatomy will allow relationships between disparate types of data to be discovered.

The methods used generalize well beyond the cardiovascular system and so this paper serves as a model for a more general framework.

Planum Temporale Shape Analysis

Employer: Center for Imaging Sciences
Position: Undergraduate Researcher

This ongoing project uses state-of-the-art tools in computational anatomy to analyze differences in the shape of the Planum Temporale in schizophrenic patients.  The PT is believed to be involved in locating audio in space.

In addition to using the Large Deformation Diffeomorphic Metric Mapping (lddmm) algorithm for surfaces, developed at CIS, I have written several utility scripts in Matlab and C to process the data.

Introduction to Metric Pattern Theory

Employer: Center for Educational Resources
Position: Technology Fellow (awarded twice)

Along with professor Tilak Ratnanather, I was awarded two Technology Fellowships to develop interactive educational materials for metric pattern theory.  The workbooks I developed are an integral part of the educational component both of Center for Imaging Sciences and the Brain Sciences Institute.