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Automatic detection and characterization of quantitative phase images of thalassemic red blood cells using a mask region-based convolutional neural network
Significance: Label-free quantitative phase imaging is a promising technique for the automatic detection of abnormal red blood cells (RBCs) in real time. Although deep-learning techniques can accurately detect abnormal RBCs from quantitative phase images efficiently, their applications in diagnostic...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Society of Photo-Optical Instrumentation Engineers
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7665881/ https://www.ncbi.nlm.nih.gov/pubmed/33188571 http://dx.doi.org/10.1117/1.JBO.25.11.116502 |