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

We present a novel approach to identify various cell lines and primary cells based on their identity and state using images acquired across various imaging platforms which vary in resolution, magnification and image quality. Despite these differences, we could show that our efficient, adaptive k-nearest neighbor search pipeline can be applied on a large image dataset containing different cell types and effectively differentiate between the cells and their states such as live, apoptotic or necrotic. There are several applications, particularly in distinguishing various cell populations in patient samples or monitoring therapy.

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Publication Details

Journal
Frontiers in Oncology
Published
2025-06-18
DOI
https://doi.org/10.3389/fonc.2025.1480384
Citations
2
Primary Topic
Cell Image Analysis Techniques
Type
article
Field-Weighted Citation Impact
3.27
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article

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

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2 citations
Frontiers in Oncology
Cell Image Analysis Techniques
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Leveraging a foundation model zoo for cell similarity search in oncological microscopy across devices

Jesús Duque‐Afonso, Evelyn Ullrich, Gabriel Kalweit, Joschka Boedecker, Marie Follo, Tanja Nicole Hartmann, Michael Lübbert, Diógenes Infante, Ruud Berger, Paula Silvestrini, Mehdi Naouar, Anusha Klett, Yannick Vogt, Jens Rahnfeld, Roland Mertelsmann, Elitsa Bodurova-Spassova
article en
2 citations

Abstract

We present a novel approach to identify various cell lines and primary cells based on their identity and state using images acquired across various imaging platforms which vary in resolution, magnification and image quality. Despite these differences, we could show that our efficient, adaptive k-nearest neighbor search pipeline can be applied on a large image dataset containing different cell types and effectively differentiate between the cells and their states such as live, apoptotic or necrotic. There are several applications, particularly in distinguishing various cell populations in patient samples or monitoring therapy.

Frontiers in OncologyVol. 15
Goethe University Frankfurt (DE), University of Freiburg (DE), German Cancer Research Center (DE), University Medical Center Freiburg (DE), Universidad Nacional del Litoral (AR), Bernstein Center for Computational Neuroscience Freiburg (DE), German Cancer Society (DE), Protestant University of Applied Sciences Freiburg (DE), Frankfurt Cancer Institute (DE)
Decent work and economic growth
Openalex Percentile: Top 8%
Cell Image Analysis Techniques
3.27
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