Ji, Yanni and Cutiongco, Marie F.A. and Jensen, Bjørn Sand and Yuan, Ke (2025) Generating realistic single-cell images from CellProfiler representations. Medical Image Analysis. ISSN 1361-8415 (In Press)
AI Summary:
The proposed CellProfiler to image CP2Image model can directly generate realistic cell images from CellProfiler representations. The model is robust to different architectures and well preserves biological information during the generation process.AI Topics:
High-throughput imaging techniques acquire large amounts of images efficiently. These images contain rich biological information including cellular processes. A common method to analyze them is to encode them into quantitative representation vectors. Generally, there are two ways to extract cell biological information into representations, hand-crafted and machine-learning. Although representations obtained from machine learning models often demonstrate commendable reconstruction performance, they lack biological interpretability. In contrast, hand-crafted representations have clear biological meanings, making them easily interpretable. However, the capability of hand-crafted representations to generate realistic images remains uncertain. In this work, we propose a CellProfiler to image (CP2Image) model capable of directly generating realistic cell images from CellProfiler representations. The proposed model is demonstrated to be robust to different architectures, including ResNet, InceptionNet and Transformer. We also show that the biological information is well preserved during the generation process. The changes in certain CellProfiler features will reflect the corresponding changes in the generated single-cell images. In addition, the CP2Image model can generate conditional phenotypes, which will ultimately help diagnostics and drug screening.
Ji, Yanni
Author
Ji, Yanni and Cutiongco, Marie F.A. and Jensen, Bjørn Sand and Yuan, Ke (2025) Generating realistic single-cell images from CellProfiler representations. Medical Image Analysis. ISSN 1361-8415 (In Press)
See full publications listCutiongco, Marie F.A.
Author
Ji, Yanni and Cutiongco, Marie F.A. and Jensen, Bjørn Sand and Yuan, Ke (2025) Generating realistic single-cell images from CellProfiler representations. Medical Image Analysis. ISSN 1361-8415 (In Press)
See full publications listJensen, Bjørn Sand
Author
Ji, Yanni and Cutiongco, Marie F.A. and Jensen, Bjørn Sand and Yuan, Ke (2025) Generating realistic single-cell images from CellProfiler representations. Medical Image Analysis. ISSN 1361-8415 (In Press)
See full publications listYuan, Ke
Author
Farndale, Lucas and Insall, Robert and Yuan, Ke (2025) TriDeNT: Triple deep network training for privileged knowledge distillation in histopathology. Medical Image Analysis, 102: 103479. ISSN 1361-8415
Ji, Yanni and Cutiongco, Marie F.A. and Jensen, Bjørn Sand and Yuan, Ke (2025) Generating realistic single-cell images from CellProfiler representations. Medical Image Analysis. ISSN 1361-8415 (In Press)
Coudray, Nicolas and Juarez, Michelle C. and Criscito, Maressa C. and Claudio Quiros, Adalberto and Wilken, Reason and Jackson Cullison, Stephanie R. and Stevenson, Mary L. and Doudican, Nicole A. and Yuan, Ke and Aquino, Jamie D. and Klufas, Daniel M. and North, Jeffrey P. and Yu, Siegrid S. and Murad, Fadi and Ruiz, Emily and Schmults, Chrysalyne D. and Cardona Machado, Cristian D. and Cañueto, Javier and Choudhary, Anirudh and Hughes, Alysia N. and Stockard, Alyssa and Leibovit-Reiben, Zachary and Mangold, Aaron R. and Tsirigos, Aristotelis and Carucci, John A. (2025) Self supervised artificial intelligence predicts poor outcome from primary cutaneous squamous cell carcinoma at diagnosis. npj Digital Medicine, 8 (1): 105. ISSN 2398-6352
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