Goda Keisuke, Di Carlo Dino, Jalali Bahram
Annu Int Conf IEEE Eng Med Biol Soc. 2013;2013:129-32. doi: 10.1109/EMBC.2013.6609454.
We present a method for ultrafast automated single-cell optical microscopy that performs blur-free image acquisition and non-stop real-time image-recording and classification of cells during high-speed flow. This method is based on a unique integration of ultrafast optical imaging, self-focusing microfluidics, optoelectronics, and information technology. To show the system's utility, we demonstrate high-throughput image-based screening of rare breast cancer cells in blood with an unprecedented throughput of 100,000 cells/s and a record false positive rate of one in a million. This method is expected to be effective for early, noninvasive, low-cost detection of cancer.
我们提出了一种用于超快速自动单细胞光学显微镜的方法，该方法可在高速流动过程中进行无模糊图像采集以及对细胞进行不间断实时图像记录和分类。此方法基于超快速光学成像、自聚焦微流体、光电子学和信息技术的独特整合。为展示该系统的实用性，我们演示了基于图像的高通量血中罕见乳腺癌细胞筛查，其通量达到前所未有的每秒100,000个细胞，且假阳性率创纪录地低至百万分之一。预计该方法对于癌症的早期、非侵入性、低成本检测将是有效的。
