Fang et al., 2022 - Google Patents
In silico labeling enables kinetic myelination assay in brightfieldFang et al., 2022
View PDF- Document ID
- 2532593852433026793
- Author
- Fang J
- Bergsdorf E
- Unterreiner V
- Greca A
- Dergai O
- Claerr I
- Luong-Nguyen N
- Galuba I
- Moutsatsos I
- Hatakeyama S
- Groot-Kormelink P
- Zeng F
- Zhang X
- Publication year
- Publication venue
- bioRxiv
External Links
Snippet
Recent advances with deep neural networks have shown the feasibility of acquiring brightfield images with transmitted light and applying in-silico labeling to predict fluorescent images. We have developed a novel in-silico labeling method based on a generative …
- 238000004166 bioassay 0 title abstract description 25
Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by the preceding groups
- G01N33/48—Investigating or analysing materials by specific methods not covered by the preceding groups biological material, e.g. blood, urine; Haemocytometers
- G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
- G01N33/5005—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells
- G01N33/5008—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells for testing or evaluating the effect of chemical or biological compounds, e.g. drugs, cosmetics
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