| Literature DB >> 22753513 |
Keisuke Goda1, Ali Ayazi, Daniel R Gossett, Jagannath Sadasivam, Cejo K Lonappan, Elodie Sollier, Ali M Fard, Soojung Claire Hur, Jost Adam, Coleman Murray, Chao Wang, Nora Brackbill, Dino Di Carlo, Bahram Jalali.
Abstract
Optical microscopy is one of the most widely used diagnostic methods in scientific, industrial, and biomedical applications. However, while useful for detailed examination of a small number (< 10,000) of microscopic entities, conventional optical microscopy is incapable of statistically relevant screening of large populations (> 100,000,000) with high precision due to its low throughput and limited digital memory size. We present an automated flow-through single-particle optical microscope that overcomes this limitation by performing sensitive blur-free image acquisition and nonstop real-time image-recording and classification of microparticles during high-speed flow. This is made possible by integrating ultrafast optical imaging technology, self-focusing microfluidic technology, optoelectronic communication technology, and information technology. To show the system's utility, we demonstrate high-throughput image-based screening of budding yeast and rare breast cancer cells in blood with an unprecedented throughput of 100,000 particles/s and a record false positive rate of one in a million.Entities:
Mesh:
Year: 2012 PMID: 22753513 PMCID: PMC3406874 DOI: 10.1073/pnas.1204718109
Source DB: PubMed Journal: Proc Natl Acad Sci U S A ISSN: 0027-8424 Impact factor: 11.205