[CCoE Notice] Cullen College Dissertation Defense Announcement - Rachel Mills

[Hutchinson, Inez A]

[Dissertation Defense Announcement at the Cullen College of Engineering]

A Visual Query-driven Search Engine for Brain Tissue Analysis

Rachel W Mills

December 4, 2023; 10:00 AM (CST)

Zoom: https://urldefense.com/v3/__https://uh-edu-cougarnet.zoom.us/j/88110213389?pwd=UkdjZkNQT29zVVhCTjZrK0dRTEM4Zz09__;!!LkSTlj0I!HCTY78-NnuZ3ZfNJZKFUoPZ1R7Ptvi5eCvx-aeG2AoIXXdVrce4YDFTKvEcNj7BxAaNO7vf0HIe4Cvpo1dNMks66MVU$ 

Meeting ID: 881 1021 3389
Passcode: 927074

Committee Chair:

Badrinath Roysam, Ph.D.

Committee Members:

Saurabh Prasad, Ph.D. | David Mayerich, Ph.D. | Hien Nguyen, Ph.D. | Dragan Maric, Ph.D.

Abstract

We present a versatile strategy for analyzing whole-slide multiplex IHC scans of brain tissue, without the confines, limitations, and programming needs of conventional script-based methods, using an alternative strategy based on a visual search engine. The engine learns the cytoarchitectural characteristics of provided training images without human effort or intervention. Next, it accepts visual queries indicating one or more cells, and/or multicellular tissue patches of interest, and retrieves a rank-ordered spatially mapped list of similar other cells or tissue patches based on cell morphologies, protein expression patterns, cytoarchitecture, myeloarchitecture, or local microvasculature, as appropriate. Retrievals from multiple queries can be co-analyzed using intuitive set-theoretic operations to generate sophisticated analyses that would ordinarily require complex programming. We envision a broad range of uses, e.g., identifying cell populations, discovering cellular/cytoarchitectural similarities and differences across brain regions, delineating brain regions, fitting/ refining/ building atlases, delineating cortical cell layers, and proofreading segmentation results.

[Engineered For What's Next]

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