PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
We have recently demonstrated a high throughput three-dimensional (3D) image flow cytometry method, in which a machine-learning algorithm is used to retrieve the 3D refractive index maps of cells from one angle-multiplexing interferogram. Using this system, we have imaged flowing red blood cells and NIH/3T3 cells with a throughput of more than < 10,000 volumes/second. To further demonstrate its potential on cell phenotyping for clinical testing, we plan to apply this platform to image large populations of various cell types and extracting their morphological and biophysical parameters.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.