Self-Learning Microfluidic Platform for Single-Cell Imaging and Classification in Flow.

ABSTRACT: Single-cell analysis commonly requires the confinement of cell suspensions in an analysis chamber or the precise positioning of single cells in small channels. Hydrodynamic flow focusing has been broadly utilized to achieve stream confinement in microchannels for such applications. As imaging flow cytometry gains popularity, the need for imaging-compatible microfluidic devices that allow for precise confinement of single cells in small volumes becomes increasingly important. At the same time, high-throughput single-cell imaging of cell populations produces vast amounts of complex data, which gives rise to the need for versatile algorithms for image analysis. In this work, we present a microfluidics-based platform for single-cell imaging in-flow and subsequent image analysis using variation

SUBMITTER: Constantinou I 

PROVIDER: S-EPMC6563144 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature