التفاصيل البيبلوغرافية
| العنوان: |
pyPOCQuant — A tool to automatically quantify Point-Of-Care Tests from images |
| المؤلفون: |
Andreas P. Cuny, Fabian Rudolf, Aaron Ponti |
| المصدر: |
SoftwareX, Vol 15, Iss , Pp 100710- (2021) |
| بيانات النشر: |
Elsevier, 2021. |
| سنة النشر: |
2021 |
| المجموعة: |
LCC:Computer software |
| مصطلحات موضوعية: |
Lateral flow assay (LFA), Lateral flow immunoassay (LFIA), Point of care test (POCT), Test line quantification, Readout zone quantification, Diagnostics, Computer software, QA76.75-76.765 |
| الوصف: |
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. |
| نوع الوثيقة: |
article |
| وصف الملف: |
electronic resource |
| اللغة: |
English |
| تدمد: |
2352-7110 |
| Relation: |
http://www.sciencedirect.com/science/article/pii/S2352711021000558; https://doaj.org/toc/2352-7110 |
| DOI: |
10.1016/j.softx.2021.100710 |
| URL الوصول: |
https://doaj.org/article/9d67079b65164efabd2dba93c0f974c5 |
| رقم الانضمام: |
edsdoj.9d67079b65164efabd2dba93c0f974c5 |
| قاعدة البيانات: |
Directory of Open Access Journals |
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