
USC researchers used AI to analyze MRI scans and uncover the genetic architecture of the brain's corpus callosum.
Key Details
- 1Researchers analyzed brain MRI and genetic data from over 50,000 individuals worldwide.
- 2A novel AI tool was developed to automatically locate and measure the corpus callosum in MRI scans.
- 3Dozens of genetic regions affecting the size and thickness of the corpus callosum and subregions were identified.
- 4Distinct gene sets were found to govern area versus thickness, relating to brain function and development.
- 5The new AI tool is being made publicly available for research use, accelerating future discoveries.
Why It Matters
This research exemplifies the power of AI in large-scale neuroimaging analysis, connecting genetic factors to brain structure with direct implications for studying mental health and neurological disorders. Making the AI tool available to the community could further advance imaging genetics, precision diagnostics, and brain disease research.

Source
EurekAlert
Related News

•EurekAlert
AI Repurposes Routine CT Scans for Osteoporosis Detection
AI algorithms can extract bone density data from routine CT scans to identify osteoporosis, enabling opportunistic screening.

•EurekAlert
AI Outperforms Radiologists in Detecting Hidden Airway Objects on Chest CT
Southampton researchers developed an AI that surpassed radiologists in detecting hard-to-see airway obstructions on chest CT scans.

•EurekAlert
AI Method Automates X-ray Absorption Spectroscopy for Material Analysis
Researchers have developed an AI-based approach to automate and enhance the analysis of X-ray absorption spectroscopy (XAS) data for materials science.