Automated Image Collection for Neuroimaging Research
Author Information
Author(s): Viangteeravat Teeradache, Anyanwu Matthew N, Ra Nagisetty Venkateswara, Kuscu Emin
Primary Institution: Clinical and Translational Science Institute University of Tennessee Health Science Center
Hypothesis
Can automated processes improve the generation and analysis of massive image collections in neuroimaging?
Conclusion
The proposed algorithm automates the creation of large image collections, facilitating easier analysis for clinical research.
Supporting Evidence
- The algorithm automates the creation of large image collections.
- Pivot technology allows for interactive analysis of high-resolution images.
- The study utilized a dataset of 1087 genes co-expressed with Dab2.
Takeaway
This study shows how computers can help scientists look at lots of brain images quickly and easily, making it easier to find important patterns.
Methodology
The study used Microsoft Live Labs Pivot technology to create and analyze image collections from the Allen Brain Atlas.
Limitations
The current implementation may not fully address all analytical needs and requires further development for advanced statistical functions.
Digital Object Identifier (DOI)
Want to read the original?
Access the complete publication on the publisher's website