Synthetic data enables human-grade microtubule analysis with foundation models for segmentation.
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| Title: | Synthetic data enables human-grade microtubule analysis with foundation models for segmentation. |
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| Authors: | Koddenbrock M; KI Werkstatt, Hochschule für Technik und Wirtschaft Berlin (HTW), Berlin, Germany., Westerhoff J; Berliner Hochschule für Technik (BHT), Berlin, Germany., Fachet D; Max Planck Institute for Infection Biology, Berlin, Germany., Reber S; Berliner Hochschule für Technik (BHT), Berlin, Germany.; Max Planck Institute for Infection Biology, Berlin, Germany., Gers FA; Berliner Hochschule für Technik (BHT), Berlin, Germany., Rodner E; KI Werkstatt, Hochschule für Technik und Wirtschaft Berlin (HTW), Berlin, Germany.; Merantix Momentum GmbH, Berlin, Germany. |
| Source: | PLoS computational biology [PLoS Comput Biol] 2026 May 05; Vol. 22 (5), pp. e1013901. Date of Electronic Publication: 2026 May 05 (Print Publication: 2026). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Public Library of Science Country of Publication: United States NLM ID: 101238922 Publication Model: eCollection Cited Medium: Internet ISSN: 1553-7358 (Electronic) Linking ISSN: 1553734X NLM ISO Abbreviation: PLoS Comput Biol Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1553-7358 |
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| DOI: | 10.1371/journal.pcbi.1013901 |
