Brain Image Data Bank a New “Google” Tool for Doctors

January 9, 2014


When an MRI scan uncovers an unusual architecture or shape in a child’s brain, it’s cause for concern: The malformation may be a sign of disease. But deciding whether that odd-looking anatomy is worrisome or harmless can be difficult.

To help doctors reach the right decision, Johns Hopkins researchers are building a detailed digital library of MRI scans collected from children with normal and abnormal brains. The goal, the researchers say, is to give physicians a Google-like search system that will enhance the way they diagnose and treat young patients with brain disorders.

This cloud-computing project, being developed by a team of engineers and radiologists, should allow physicians to access thousands of pediatric scans to look for some that resemble their own patient’s image. The project is supported by a three-year $600,000 grant from the National Institutes of Health.

“We’re creating a pediatric brain data bank that will let doctors look at MRI brain scans of children who have already been diagnosed with illnesses like epilepsy or psychiatric disorders,” said Michael I. Miller, a lead investigator on the project. “It will provide a way to share important new discoveries about how changes in brain structures are linked to brain disorders. For the medical imaging world, this system will do what a search engine like Google does when you ask it to look for specific information on the Web.”

Miller, a pioneer in the field of computational anatomy, the technology used for “brain parsing,” is the Herschel and Ruth Seder Professor of Biomedical Engineering at Johns Hopkins Whiting School of Engineering and director of the university’s Center for Imaging Science. He also is affiliated with the university’s Institute for Computational Medicine.

Related News: 

News Release: Children’s Brain Imaging Data Bank Could Become a ‘Google’ Tool for Doctor

Video: Interview with Michael I. Miller, the Herschel and Ruth Seder Professor of Biomedical Engineering

Michael I. Millier’s Lab, the Center for Imaging Science.

The Institute for Computational Medicine


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