TY - GEN
T1 - A low-cost and simple on-chip cell counting device based on lensless imaging technology
AU - Wang, Yongliang
AU - Guo, Xiaoliang
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Cell counting is a basic and important detection technique in biomedical diagnosis. However, current cell counting devices are expensive and bulky, which are not conducive to rapid cell counting. To solve this problem, we design a low-cost and simple on-chip cell counting device based on lensless imaging technology. The device uses an ordinary white LED light and a CMOS image sensor to capture the cell image in the microfluidic chip, and uses a microcomputer - Raspberry Pi 4B for image transmission and processing. Then a self-developed processing program is designed to count the cells. In addition, the device can perform micron-scale particle imaging, which can identify microbeads of different sizes. Compared with other lensless imaging devices, our device has obvious advantages in low cost, scalability, and degree of automation, which can improve the efficiency of biological experiments, and is of great significance for expanding the population of healthcare services in the future.
AB - Cell counting is a basic and important detection technique in biomedical diagnosis. However, current cell counting devices are expensive and bulky, which are not conducive to rapid cell counting. To solve this problem, we design a low-cost and simple on-chip cell counting device based on lensless imaging technology. The device uses an ordinary white LED light and a CMOS image sensor to capture the cell image in the microfluidic chip, and uses a microcomputer - Raspberry Pi 4B for image transmission and processing. Then a self-developed processing program is designed to count the cells. In addition, the device can perform micron-scale particle imaging, which can identify microbeads of different sizes. Compared with other lensless imaging devices, our device has obvious advantages in low cost, scalability, and degree of automation, which can improve the efficiency of biological experiments, and is of great significance for expanding the population of healthcare services in the future.
KW - cell count
KW - lensless imaging technology
KW - low-cost
KW - on-chip
UR - http://www.scopus.com/inward/record.url?scp=85135395013&partnerID=8YFLogxK
U2 - 10.1109/CVIDLICCEA56201.2022.9825217
DO - 10.1109/CVIDLICCEA56201.2022.9825217
M3 - Conference contribution
AN - SCOPUS:85135395013
T3 - 2022 3rd International Conference on Computer Vision, Image and Deep Learning and International Conference on Computer Engineering and Applications, CVIDL and ICCEA 2022
SP - 559
EP - 562
BT - 2022 3rd International Conference on Computer Vision, Image and Deep Learning and International Conference on Computer Engineering and Applications, CVIDL and ICCEA 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 3rd International Conference on Computer Vision, Image and Deep Learning and International Conference on Computer Engineering and Applications, CVIDL and ICCEA 2022
Y2 - 20 May 2022 through 22 May 2022
ER -