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- Title
Automated and Reproducible Detection of Vascular Endothelial Growth Factor (VEGF) in Renal Tissue Sections.
- Authors
Macedo, Nayana Damiani; Buzin, Aline Rodrigues; de Araujo, Isabela Bastos; Nogueira, Breno Valentim; Andrade, Tadeu Uggere; Endringer, Denise Coutinho; Lenz, Dominik
- Abstract
<bold>Background: </bold>Manual analysis of tissue sections, such as for pathological diagnosis, requires an analyst with substantial knowledge and experience. Reproducible image analysis of biological samples is steadily gaining scientific importance. The aim of the present study was to employ image analysis followed by machine learning to identify vascular endothelial growth factor (VEGF) in kidney tissue that had been subjected to hypoxia.<bold>Methods: </bold>Light microscopy images of renal tissue sections stained for VEGF were analyzed. Subsequently, machine learning classified the cells as VEGF+ and VEGF- cells.<bold>Results: </bold>VEGF was detected and cells were counted with high sensitivity and specificity.<bold>Conclusion: </bold>With great clinical, diagnostic, and research potential, automatic image analysis offers a new quantitative capability, thereby adding numerical information to a mostly qualitative diagnostic approach.
- Subjects
VASCULAR endothelial growth factors
- Publication
Journal of Immunology Research, 2019, p1
- ISSN
2314-8861
- Publication type
journal article
- DOI
10.1155/2019/7232781