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Intelligent Image-Activated Cell Sorting
- Source :
- Cell. 175(1):266-276.e13
- Publication Year :
- 2018
- Publisher :
- Elsevier BV, 2018.
-
Abstract
- 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 highly versatile and expected to enable machine-based scientific discovery in biological, pharmaceutical, and medical sciences.<br />世界初のIntelligent Image-Activated Cell Sorterを開発 --細胞画像の深層学習により高速細胞選抜を実現--. 京都大学プレスリリース. 2018-09-05.
- Subjects :
- 0301 basic medicine
cellular morphology
Distributed computing
Scientific discovery
convolutional neural network
Image processing
02 engineering and technology
Biology
machine intelligence
Convolutional neural network
high-throughput screening
General Biochemistry, Genetics and Molecular Biology
Image (mathematics)
ghigh-throughput microscopy
03 medical and health sciences
Data acquisition
cellular heterogeneity
Image Processing, Computer-Assisted
Animals
Humans
Intracellular protein
Sorting
deep learning
image-activated cell sortin
Cell sorting
021001 nanoscience & nanotechnology
Flow Cytometry
High-Throughput Screening Assays
030104 developmental biology
0210 nano-technology
Subjects
Details
- Language :
- English
- ISSN :
- 00928674
- Volume :
- 175
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- Cell
- Accession number :
- edsair.doi.dedup.....b027c093b4b015ab3c29cc221f460382