Leveraging a foundation model zoo for cell similarity search in oncological microscopy across devices

Leveraging a foundation model zoo for cell similarity search in oncological microscopy across devices

BackgroundCellular imaging analysis using the traditional retrospective approach is extremely time-consuming and labor-intensive. Although AI-based solutions are available, these approaches rely heavily on supervised learning techniques that require high quality, large labeled datasets from the same...

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Bibliographic Details
Main Authors: Gabriel Kalweit, Anusha Klett, Paula Silvestrini, Jens Rahnfeld, Mehdi Naouar, Yannick Vogt, Diana Infante, Rebecca Berger, Jesús Duque-Afonso, Tanja Nicole Hartmann, Marie Follo, Elitsa Bodurova-Spassova, Michael Lübbert, Roland Mertelsmann, Joschka Boedecker, Evelyn Ullrich, Maria Kalweit
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-06-01
Series:Frontiers in Oncology
Subjects:
artificial intelligence
deep learning
foundation models
nearest neighbor search
cell imaging
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2025.1480384/full
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