FiloAnalyzer: a deep learning approach for cell filopodia segmentation.
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| Title: | FiloAnalyzer: a deep learning approach for cell filopodia segmentation. |
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| Authors: | Pastore VP; MaLGa-DIBRIS, University of Genoa, Genoa, Italy. vito.paolo.pastore@unige.it.; Center for Cellular Construction, San Francisco, CA, USA. vito.paolo.pastore@unige.it., Rorato R; MaLGa-DIBRIS, University of Genoa, Genoa, Italy., Touijer L; MaLGa-DIBRIS, University of Genoa, Genoa, Italy., Via RD; MaLGa-DIBRIS, University of Genoa, Genoa, Italy., Odone F; MaLGa-DIBRIS, University of Genoa, Genoa, Italy., Galli LM; Department of Biology, San Francisco State University, San Francisco, CA, USA.; Center for Cellular Construction, San Francisco, CA, USA., Burrus LW; Department of Biology, San Francisco State University, San Francisco, CA, USA.; Center for Cellular Construction, San Francisco, CA, USA., Bianco S; Center for Cellular Construction, San Francisco, CA, USA.; Altos Labs, Institute of Computation, Redwood City, CA, USA. |
| Source: | BMC bioinformatics [BMC Bioinformatics] 2026 Apr 24; Vol. 27 (1). Date of Electronic Publication: 2026 Apr 24. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: BioMed Central Country of Publication: England NLM ID: 100965194 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-2105 (Electronic) Linking ISSN: 14712105 NLM ISO Abbreviation: BMC Bioinformatics Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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