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Big Data Systems for Medical Imaging

Primary Investigator/s:
Bennett Landman

Brief Description of Project:
The research objective of this proposal is to discover genetic and environmental factors that influence an individual’s brain development and characterize the developing human brain through personal developmental trajectories. To accomplish this goal, new informatics technologies will be created to enable (1) image processing and segmentation based on image content in the context of heterogeneous, low quality, and error prone data with minimal human oversight and (2) routine archival, query, and image processing of large medical imaging datasets.

This research focuses on developing novel data models that will investigate the interesting, but hitherto, unexplored relationships between medical imaging standards and big data architectures that are derived from social network and e-commerce communities. These new data models, realized in the context of big data architectures, will result in infrastructure that has the potential to provide practical access to petabyte imaging archives, integrate with existing data workflows, and effectively function with commodity hardware. The informatics tools will result from the scientific exploration and will enable researchers to harness the power of either private clusters or commercial cloud services to analyze large imaging archives using available image computing software and standard data sources.

Desired Qualifications:
SQL, Java, C/C++ programming

Nature of Supervision:
PI and Graduate Student

A Brief Research Plan (period is for 10 weeks):
Weeks 1-2: Literature and Technical Review
Weeks 3-4: Prototype planning
Weeks 5-7: Implementation
Weeks 8-9: Testing / Validation
Week 10: Write-up and Documentation

Number of Slots: 2

Contact Information
Bennett Landman
Electrical Engineering & Computer Science