Quantitative analysis of the 2D tissue skin layer with fluorescent dyes
Issued Date
2022-01-01
Resource Type
Scopus ID
2-s2.0-85136162003
Journal Title
2022 19th International Joint Conference on Computer Science and Software Engineering, JCSSE 2022
Rights Holder(s)
SCOPUS
Bibliographic Citation
2022 19th International Joint Conference on Computer Science and Software Engineering, JCSSE 2022 (2022)
Suggested Citation
Chaiprasongsuk R., Achararit P., Jarutatsanangkoon P., Nonthasaen P., Mahikul W., Chaiprasongsuk A., Panich U., Prombut P. Quantitative analysis of the 2D tissue skin layer with fluorescent dyes. 2022 19th International Joint Conference on Computer Science and Software Engineering, JCSSE 2022 (2022). doi:10.1109/JCSSE54890.2022.9836243 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/84375
Title
Quantitative analysis of the 2D tissue skin layer with fluorescent dyes
Author's Affiliation
Other Contributor(s)
Abstract
Development of an automated process for quantifying proteins in multiple layers of skin is essential to research in the field of cell biology. Researchers aimed to quantify the cell density and levels of biomarkers on tissue samples. Immunofluorescence tissue staining is one of the standard methods used for the protein detection by tagging with the fluorescein isothiocyanate (FITC), the green fluorescent agent. Recently, the single-cell (monolayer tissue) analysis software automation has been obtained to quantify the protein levels. However, there are limitations for the analysis of overlapping multilayer tissue. Since the automatic analysis cannot be operated on the rough and muti-layered surface, the analysis is then manually performed using ImageJ software which process more than 5 minutes/image. Problems arise when many images of tissues need to be analyzed. Therefore, an automatic process has been developed for the image analysis to reduce time and error. This study developed the automatic process by adjusting the pixel intensity and splitting into the RGB channels and converting into gray with different intensities. The intensity can be measured on grayscale from 0 to 255 units based on the KODAK grayscale zone. The FITC staining is converted to be the grayscale intensity for the pixel intensity calculation. The gray level < 25 units was setup to be the exclusion criteria to solve the problem of over-exposure due to background noise. Therefore, this automated data processing enhances the technical capabilities and computational accuracy, which proposes an alternative approach to improve the tissue analysis for cell biology research.