期刊
SCIENTIFIC REPORTS
卷 3, 期 -, 页码 -出版社
NATURE PORTFOLIO
DOI: 10.1038/srep01699
关键词
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资金
- Presidential Early Career Award for Scientists and Engineers
- Army Research Office Young Investigator Award
- National Science Foundation CAREER Award
- Office of Naval Research Young Investigator Award
- National Institutes of Health Director's New Innovator Award from the Office of the Director, National Institutes of Health [DP2OD006427]
- National Center for Advancing Translational Sciences UCLA CTSI Grant [UL1TR000124]
- Div Of Chem, Bioeng, Env, & Transp Sys
- Directorate For Engineering [0954482] Funding Source: National Science Foundation
Computational microscopy tools, in particular lensfree on-chip imaging, provide a large field-of-view along with a long depth-of-field, which makes it feasible to rapidly analyze large volumes of specimen using a compact and light-weight on-chip imaging architecture. To bring molecular specificity to this high-throughput platform, here we demonstrate the use of plasmon-resonant metallic nanoparticles to automatically recognize different cell types based on their plasmon-enhanced lensfree holograms, detected and reconstructed over a large field-of-view of e.g., similar to 24 mm(2).
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