Summary

Grant funded part-time Research Assistant of effort performing manual segmentation of tubers in tuberous sclerosis patients on MRI and implementation of an automated segmentation processing technique. This involves using algorithms or manual techniques to delineate the tuber from their surrounding environment (brain tissue in medical imaging). The work will be supervised by co-investigator radiologist Dr. Kralik.

Patients with a diagnosis of tuberous sclerosis have lesions in the brain known as tubers. These tubers are regions of disorganized brain tissue and are the cause of epilepsy in these patients. Tuber segmentation refers to identifying and delineating/segmenting these lesions on imaging studies (specifically MRI in this research). Segmentation of tubers allows for determination of the severity of the disease and allows for localization with respect to ares of the brain that perform specific functions. Segmentation can be performed manually by tracing the margins of the tubers as well as automated using advanced image processing algorithms. Manual segmentation and implementation of an automated processing technique is the primary focus of the research assistant.

Job Duties

• Perform manual and automated segmentation of abnormal brain regions under supervision by Dr. Kralik. Automated segmentation processing technique will require advanced computer programming skills to implement an open source processing technique that relies on Linux based operating system and entry of command lines to process.
• Transfer data to collaborators when needed.
• Assist in research data processing as assigned.
• Attend research meetings through video conference.
• Communicate to the research team project updates and progress on a regular basis by email.

Minimum Qualifications

• Bachelor's degree in a Basic Science or a related field.
• Two years of relevant experience.

Preferred Qualifications

• Master's degree in basic science or a related field.
• Familiarity with Linux computer systems