Intelligent image-activated cell sorting and beyond

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Keisuke Goda
Graduate School of Science
A fundamental challenge of biology is to understand the vast heterogeneity of cells, particularly how cellular composition, structure, and morphology are linked to cellular physiology. Unfortunately, conventional technologies are limited in uncovering these relations. We present a machine-intelligence technology based on a radically different architecture that realizes real-time image-based intelligent cell sorting at an unprecedented rate. This technology, which we refer to as intelligent image-activated cell sorting, integrates high-throughput cell microscopy, focusing, and sorting on a hybrid software-hardware data-management infrastructure, enabling real-time automated operation for data acquisition, data processing, decision-making, and actuation. We use it to demonstrate real-time sorting of microalgal and blood cells based on intracellular protein localization and cell-cell interaction from large heterogeneous populations for studying photosynthesis and atherothrombosis, respectively. The technology is a resource for everyone who wants to make new discoveries in biological, pharmaceutical, and medical sciences. To assist such researchers, we are launching an open innovation platform, and launching a start-up to turn it into a product.
Overview of the Intelligent Image-Activated Cell Sorter
Future plans

Research collaborators

- Professor Sotaro Uemura, Graduate School of Science
- Professor Robert Campbel, Graduate School of Science
- Professor Yoshihiro Kawahara, Graduate School of Information Science and Technology
- Professor Yutaka Yatomi, Graduate School of Medicine
- Professor Yoshikazu Ohya, Graduate School of Frontier Sciences
- Associate Professor Yuto Kitamura, Graduate School of Education

Related publications

- Nitta et al. Intelligent image-activated cell sorting. Cell 175, 266-276 (2018)


  • Keisuke Goda
  • Tel: +81-3-5841-4329
  • Email: goda[at]
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