Neuromorphic-enabled video-activated cell sorting
Abstract Imaging flow cytometry allows image-activated cell sorting (IACS) with enhanced feature dimensions in cellular morphology, structure, and composition. However, existing IACS frameworks suffer from the challenges of 3D information loss and processing latency dilemma in real-time sorting oper...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2024-12-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-024-55094-0 |
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| _version_ | 1841559366585548800 |
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| author | Weihua He Junwen Zhu Yongxiang Feng Fei Liang Kaichao You Huichao Chai Zhipeng Sui Haiqing Hao Guoqi Li Jingjing Zhao Lei Deng Rong Zhao Wenhui Wang |
| author_facet | Weihua He Junwen Zhu Yongxiang Feng Fei Liang Kaichao You Huichao Chai Zhipeng Sui Haiqing Hao Guoqi Li Jingjing Zhao Lei Deng Rong Zhao Wenhui Wang |
| author_sort | Weihua He |
| collection | DOAJ |
| description | Abstract Imaging flow cytometry allows image-activated cell sorting (IACS) with enhanced feature dimensions in cellular morphology, structure, and composition. However, existing IACS frameworks suffer from the challenges of 3D information loss and processing latency dilemma in real-time sorting operation. Herein, we establish a neuromorphic-enabled video-activated cell sorter (NEVACS) framework, designed to achieve high-dimensional spatiotemporal characterization content alongside high-throughput sorting of particles in wide field of view. NEVACS adopts event camera, CPU, spiking neural networks deployed on a neuromorphic chip, and achieves sorting throughput of 1000 cells/s with relatively economic hybrid hardware solution (~$10 K for control) and simple-to-make-and-use microfluidic infrastructures. Particularly, the application of NEVACS in classifying regular red blood cells and blood-disease-relevant spherocytes highlights the accuracy of using video over a single frame (i.e., average error of 0.99% vs 19.93%), indicating NEVACS’ potential in cell morphology screening and disease diagnosis. |
| format | Article |
| id | doaj-art-7391e89c79d94f2dbedd6ea51fb72be9 |
| institution | Kabale University |
| issn | 2041-1723 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj-art-7391e89c79d94f2dbedd6ea51fb72be92025-01-05T12:34:33ZengNature PortfolioNature Communications2041-17232024-12-0115111610.1038/s41467-024-55094-0Neuromorphic-enabled video-activated cell sortingWeihua He0Junwen Zhu1Yongxiang Feng2Fei Liang3Kaichao You4Huichao Chai5Zhipeng Sui6Haiqing Hao7Guoqi Li8Jingjing Zhao9Lei Deng10Rong Zhao11Wenhui Wang12State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua UniversityState Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua UniversityState Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua UniversityState Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua UniversitySoftware School, Tsinghua UniversityState Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua UniversityState Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua UniversityState Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua UniversityInstitute of Automation, Chinese Academy of SciencesInstitute of Medical Equipment Science and Engineering, Huazhong University of Science and TechnologyCenter for Brain-Inspired Computing Research (CBICR), Beijing Advanced Innovation Center for Integrated Circuits, Optical Memory National Engineering Research Center, & Department of Precision Instrument, Tsinghua UniversityCenter for Brain-Inspired Computing Research (CBICR), Beijing Advanced Innovation Center for Integrated Circuits, Optical Memory National Engineering Research Center, & Department of Precision Instrument, Tsinghua UniversityState Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instrument, Tsinghua UniversityAbstract Imaging flow cytometry allows image-activated cell sorting (IACS) with enhanced feature dimensions in cellular morphology, structure, and composition. However, existing IACS frameworks suffer from the challenges of 3D information loss and processing latency dilemma in real-time sorting operation. Herein, we establish a neuromorphic-enabled video-activated cell sorter (NEVACS) framework, designed to achieve high-dimensional spatiotemporal characterization content alongside high-throughput sorting of particles in wide field of view. NEVACS adopts event camera, CPU, spiking neural networks deployed on a neuromorphic chip, and achieves sorting throughput of 1000 cells/s with relatively economic hybrid hardware solution (~$10 K for control) and simple-to-make-and-use microfluidic infrastructures. Particularly, the application of NEVACS in classifying regular red blood cells and blood-disease-relevant spherocytes highlights the accuracy of using video over a single frame (i.e., average error of 0.99% vs 19.93%), indicating NEVACS’ potential in cell morphology screening and disease diagnosis.https://doi.org/10.1038/s41467-024-55094-0 |
| spellingShingle | Weihua He Junwen Zhu Yongxiang Feng Fei Liang Kaichao You Huichao Chai Zhipeng Sui Haiqing Hao Guoqi Li Jingjing Zhao Lei Deng Rong Zhao Wenhui Wang Neuromorphic-enabled video-activated cell sorting Nature Communications |
| title | Neuromorphic-enabled video-activated cell sorting |
| title_full | Neuromorphic-enabled video-activated cell sorting |
| title_fullStr | Neuromorphic-enabled video-activated cell sorting |
| title_full_unstemmed | Neuromorphic-enabled video-activated cell sorting |
| title_short | Neuromorphic-enabled video-activated cell sorting |
| title_sort | neuromorphic enabled video activated cell sorting |
| url | https://doi.org/10.1038/s41467-024-55094-0 |
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