| Project/Area Number |
26820158
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Measurement engineering
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| Research Institution | Hiroshima University |
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Principal Investigator |
Gu Qingyi 広島大学, 工学(系)研究科(研究院), 特任准教授 (30713979)
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| Project Period (FY) |
2014-04-01 – 2016-03-31
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| Project Status |
Completed (Fiscal Year 2015)
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| Budget Amount *help |
¥3,900,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥900,000)
Fiscal Year 2015: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
Fiscal Year 2014: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
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| Keywords | High-speed vision / Cell sorting / Hardware implementation / frame-straddling camera / lab-on-a-chip / cell-based labeling / high speed vision |
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| Outline of Final Research Achievements |
In this research project, we have achieved high-frame-rate recognition of cells fast-flowing in microchannels toward ultra-fast cell sorting by implementing a parallel multi-object feature extraction algorithm on a frame-straddling high-speed vision platform. Image-based cell features can be extracted in real-time by using hardware circuits. Recognition and classification of cells can be performed in real-time. High resolution ROI regions of fast-flowing cells in microchannels could be stored and analyzed at 1000 fps or higher. And ultra-fast analysis, inspection, and cell sorting could be achieved to increase production efficiency in bio-assembling. Lab-on-a-chip practitioners can easily apply it to real-time cell sorting of cells fast-flowing in microchannels, such as red blood or iPS cells.
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