Deep Visual Proteomics defines single-cell identity and heterogeneity
2022 · Nature Biotechnology · 476 citations
https://doi.org/10.1038/s41587-022-01302-5
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Réka Hollandi
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Réka Hollandi is an academic researcher from HUN-REN Szegedi Biológiai Kutatóközpont. The author has contributed to research in topics: Cell Image Analysis Techniques & Image Processing Techniques and Applications & AI in cancer detection. The author has an h-index of 12, co-authored 24 publications.
ORCID: 0000-0002-4052-6846Papers by this author
worksnucleAIzer: A Parameter-free Deep Learning Framework for Nucleus Segmentation Using Image Style Transfer
2020 · Cell Systems · 269 citations
https://doi.org/10.1016/j.cels.2020.04.003
Test-time augmentation for deep learning-based cell segmentation on microscopy images
2020 · Scientific Reports · 202 citations
https://doi.org/10.1038/s41598-020-61808-3
OpSeF: Open Source Python Framework for Collaborative Instance Segmentation of Bioimages
2020 · Frontiers in Bioengineering and Biotechnology · 18 citations
https://doi.org/10.3389/fbioe.2020.558880
Image-based and machine learning-guided multiplexed serology test for SARS-CoV-2
2023 · Cell Reports Methods · 7 citations
https://doi.org/10.1016/j.crmeth.2023.100565
Establishment of an imaging-based screening pipeline for the identification of human ribosome biogenesis inhibitors
2025 · BMC Biology · 0 citations
https://doi.org/10.1186/s12915-025-02425-2
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