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Image-analysis based readout method for biochip: Automated quantification of immunomagnetic beads, micropads and patient leukemia cell.

Authors :
Uslu F
Icoz K
Tasdemir K
Doğan RS
Yilmaz B
Source :
Micron (Oxford, England : 1993) [Micron] 2020 Jun; Vol. 133, pp. 102863. Date of Electronic Publication: 2020 Mar 20.
Publication Year :
2020

Abstract

For diagnosing and monitoring the progress of cancer, detection and quantification of tumor cells is utmost important. Beside standard bench top instruments, several biochip-based methods have been developed for this purpose. Our biochip design incorporates micron size immunomagnetic beads together with micropad arrays, thus requires automated detection and quantification of not only cells but also the micropads and the immunomagnetic beads. The main purpose of the biochip is to capture target cells having different antigens simultaneously. In this proposed study, a digital image processing-based method to quantify the leukemia cells, immunomagnetic beads and micropads was developed as a readout method for the biochip. Color, size-based object detection and object segmentation methods were implemented to detect structures in the images acquired from the biochip by a bright field optical microscope. It has been shown that manual counting and flow cytometry results are in good agreement with the developed automated counting. Average precision is 85 % and average error rate is 13 % for all images of patient samples, average precision is 99 % and average error rate is 1% for cell culture images. With the optimized micropad size, proposed method can reach up to 95 % precision rate for patient samples with an execution time of 90 s per image.<br />Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.<br /> (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Details

Language :
English
ISSN :
1878-4291
Volume :
133
Database :
MEDLINE
Journal :
Micron (Oxford, England : 1993)
Publication Type :
Academic Journal
Accession number :
32234685
Full Text :
https://doi.org/10.1016/j.micron.2020.102863