AI Tool Automates 3D Analysis of Cochlear Stereocilia

The VASCilia platform uses deep learning to accelerate stereocilia imaging analysis, aiding research into hearing loss and gene therapy.

Published on Feb. 11, 2026

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Researchers at the University of California San Diego have developed an artificial intelligence tool called VASCilia that automates the 3D analysis of cochlear hair cells, a process critical for understanding hearing function and developing new treatments for hearing loss. The tool accelerates the imaging process by a factor of 50 and provides detailed views of stereocilia, the bundles of protrusions within the cochlea that detect sound.

Why it matters

Understanding how stereocilia bundles get disorganized over time or after exposure to certain environmental stresses is very important in hearing loss research. VASCilia can also help measure the effectiveness of gene therapies designed to reverse hearing loss by providing consistent and accurate quantification of a large number of cells.

The details

VASCilia uses five deep learning-based models trained on expert-annotated datasets from mice to automate what was previously a slow process of manually interpreting microscopic images of hair cell bundles. The platform can detect and quantify subtle patterns of cellular disorganization that are difficult for humans to measure manually.

  • VASCilia was developed by a team including postdoctoral scholar Yasmin Kassim.

The players

Uri Manor

A biological sciences assistant professor at UC San Diego who says understanding how stereocilia bundles get disorganized is very important in hearing loss research.

Yasmin Kassim

A postdoctoral scholar and computer scientist who is a Schmidt AI postdoctoral fellow and says VASCilia has reduced the time to analyze the length of these cells by a factor of 50.

University of California San Diego

The institution where the researchers developed the VASCilia AI tool.

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What they’re saying

“Understanding how stereocilia bundles get disorganized over time, or after exposure to certain environmental stresses, is very important in hearing loss research. We would like to more fully understand how these patterns are disrupted during disease, for hearing research on noise damage and aging.”

— Uri Manor, Biological sciences assistant professor at UC San Diego (University of California San Diego)

“There are children who were born deaf that can now hear because of gene therapy and we expect those treatments for hearing loss to grow. For gene therapy experiments VASCilia allows us to measure all the cells and we can quantify them very consistently and accurately.”

— Uri Manor, Biological sciences assistant professor at UC San Diego (University of California San Diego)

“We've reduced the amount of time it takes to analyze the length of these cells by a factor of 50, enabling many additional 2D and 3D quantitative measurements that can be acquired in minutes—work that would otherwise require years of manual analysis. VASCilia can also detect and quantify subtle patterns of cellular disorganization that are difficult for humans to measure manually.”

— Yasmin Kassim, Computer scientist and Schmidt AI postdoctoral fellow (University of California San Diego)

What’s next

The researchers have made VASCilia open-source with the hope of facilitating the creation of a large-scale atlas of cochlea hair cell images to further support advances within the hearing research community.

The takeaway

This AI tool represents a significant advancement in the field of hearing loss research, as it dramatically accelerates the analysis of critical hair cell structures and could help enable new gene therapy treatments for hearing impairment.