The groups around Atsushi YASUMOTO and Yutaka YATOMI developed a rapid and reliable method to detect platelet clumps in human blood, indicators for potential thrombosis. The method is based optofluidic time-stretch microscopy on a microfluidic chip operating at a high throughput of 10000 blood cells per second. By performing cell classification with machine learning, aggregated platelets could be differentiated from single platelets and white blood cells with high specificity and sensitivity of over 96 %.

JST news release, June 23, 2017