| Autor: |
Andreas P. Cuny, Fabian Rudolf, Aaron Ponti |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
|
| Zdroj: |
SoftwareX, Vol 15, Iss , Pp 100710- (2021) |
| Druh dokumentu: |
article |
| ISSN: |
2352-7110 |
| DOI: |
10.1016/j.softx.2021.100710 |
| Popis: |
Lateral flow Point-Of-Care Tests (POCTs) are a valuable tool for rapidly detecting pathogens and the associated immune response in humans and animals. In the context of the SARS-CoV-2 pandemic, they offer rapid on-site diagnostics and can relieve centralized laboratory testing sites, thus freeing resources that can be focused on especially vulnerable groups. However, visual interpretation of the POCT test lines is subjective, error prone and only qualitative. Here we present pyPOCQuant, an open-source tool implemented in Python 3 that can robustly and reproducibly analyze POCTs from digital images and return an unbiased and quantitative measurement of the POCT test lines. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
