FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3211465462> ?p ?o ?g. }

• W3211465462 endingPage "635" @default.
• W3211465462 startingPage "626" @default.
• W3211465462 abstract "Macrophages play an important role in the adaptive immune system. Their ability to neutralize cellular targets through Fc receptor-mediated phagocytosis has relied upon immunotherapy that has become of particular interest for the treatment of cancer and autoimmune diseases. A detailed investigation of phagocytosis is the key to the improvement of the therapeutic efficiency of existing medications and the creation of new ones. A promising method for studying the process is imaging flow cytometry (IFC) that acquires thousands of cell images per second in up to 12 optical channels and allows multiparametric fluorescent and morphological analysis of samples in the flow. However, conventional IFC data analysis approaches are based on a highly subjective manual choice of masks and other processing parameters that can lead to the loss of valuable information embedded in the original image. Here, we show the application of a Faster region-based convolutional neural network (CNN) for accurate quantitative analysis of phagocytosis using imaging flow cytometry data. Phagocytosis of erythrocytes by peritoneal macrophages was chosen as a model system. CNN performed automatic high-throughput processing of datasets and demonstrated impressive results in the identification and classification of macrophages and erythrocytes, despite the variety of shapes, sizes, intensities, and textures of cells in images. The developed procedure allows determining the number of phagocytosed cells, disregarding cases with a low probability of correct classification. We believe that CNN-based approaches will enable powerful in-depth investigation of a wide range of biological processes and will reveal the intricate nature of heterogeneous objects in images, leading to completely new capabilities in diagnostics and therapy." @default.
• W3211465462 created "2021-11-22" @default.
• W3211465462 creator A5007162295 @default.
• W3211465462 creator A5056088168 @default.
• W3211465462 creator A5074297438 @default.
• W3211465462 creator A5083645854 @default.
• W3211465462 creator A5090597738 @default.
• W3211465462 date "2021-11-18" @default.
• W3211465462 modified "2023-10-01" @default.
• W3211465462 title "Imaging flow cytometry data analysis using convolutional neural network for quantitative investigation of phagocytosis" @default.
• W3211465462 cites W1967454795 @default.
• W3211465462 cites W1987333329 @default.
• W3211465462 cites W2009489065 @default.
• W3211465462 cites W2014379848 @default.
• W3211465462 cites W2014869316 @default.
• W3211465462 cites W2054323370 @default.
• W3211465462 cites W2060328411 @default.
• W3211465462 cites W2075720054 @default.
• W3211465462 cites W2099864579 @default.
• W3211465462 cites W2183182206 @default.
• W3211465462 cites W2346609893 @default.
• W3211465462 cites W2461073387 @default.
• W3211465462 cites W2521417891 @default.
• W3211465462 cites W2546215193 @default.
• W3211465462 cites W2747948215 @default.
• W3211465462 cites W2750796620 @default.
• W3211465462 cites W2772400299 @default.
• W3211465462 cites W2785880648 @default.
• W3211465462 cites W2790604607 @default.
• W3211465462 cites W2888971284 @default.
• W3211465462 cites W2889672357 @default.
• W3211465462 cites W2903863974 @default.
• W3211465462 cites W2905502540 @default.
• W3211465462 cites W2907491052 @default.
• W3211465462 cites W2909504167 @default.
• W3211465462 cites W2927199411 @default.
• W3211465462 cites W2963459241 @default.
• W3211465462 cites W2975394797 @default.
• W3211465462 cites W2980464820 @default.
• W3211465462 cites W2981235339 @default.
• W3211465462 cites W2989014648 @default.
• W3211465462 cites W2989948200 @default.
• W3211465462 cites W2991472813 @default.
• W3211465462 cites W2993189425 @default.
• W3211465462 cites W2996124455 @default.
• W3211465462 cites W2999116898 @default.
• W3211465462 cites W3005375881 @default.
• W3211465462 cites W3008977000 @default.
• W3211465462 cites W3013335580 @default.
• W3211465462 cites W3018961825 @default.
• W3211465462 cites W3040142808 @default.
• W3211465462 cites W3043306461 @default.
• W3211465462 cites W3049661244 @default.
• W3211465462 cites W3080569962 @default.
• W3211465462 cites W3087807709 @default.
• W3211465462 cites W3203222489 @default.
• W3211465462 doi "https://doi.org/10.1002/bit.27986" @default.
• W3211465462 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/34750809" @default.
• W3211465462 hasPublicationYear "2021" @default.
• W3211465462 type Work @default.
• W3211465462 sameAs 3211465462 @default.
• W3211465462 citedByCount "8" @default.
• W3211465462 countsByYear W32114654622022 @default.
• W3211465462 countsByYear W32114654622023 @default.
• W3211465462 crossrefType "journal-article" @default.
• W3211465462 hasAuthorship W3211465462A5007162295 @default.
• W3211465462 hasAuthorship W3211465462A5056088168 @default.
• W3211465462 hasAuthorship W3211465462A5074297438 @default.
• W3211465462 hasAuthorship W3211465462A5083645854 @default.
• W3211465462 hasAuthorship W3211465462A5090597738 @default.
• W3211465462 hasConcept C111919701 @default.
• W3211465462 hasConcept C153180895 @default.
• W3211465462 hasConcept C154945302 @default.
• W3211465462 hasConcept C160448771 @default.
• W3211465462 hasConcept C203014093 @default.
• W3211465462 hasConcept C2780339063 @default.
• W3211465462 hasConcept C41008148 @default.
• W3211465462 hasConcept C553184892 @default.
• W3211465462 hasConcept C70721500 @default.
• W3211465462 hasConcept C81363708 @default.
• W3211465462 hasConcept C86803240 @default.
• W3211465462 hasConcept C98045186 @default.
• W3211465462 hasConceptScore W3211465462C111919701 @default.
• W3211465462 hasConceptScore W3211465462C153180895 @default.
• W3211465462 hasConceptScore W3211465462C154945302 @default.
• W3211465462 hasConceptScore W3211465462C160448771 @default.
• W3211465462 hasConceptScore W3211465462C203014093 @default.
• W3211465462 hasConceptScore W3211465462C2780339063 @default.
• W3211465462 hasConceptScore W3211465462C41008148 @default.
• W3211465462 hasConceptScore W3211465462C553184892 @default.
• W3211465462 hasConceptScore W3211465462C70721500 @default.
• W3211465462 hasConceptScore W3211465462C81363708 @default.
• W3211465462 hasConceptScore W3211465462C86803240 @default.
• W3211465462 hasConceptScore W3211465462C98045186 @default.
• W3211465462 hasFunder F4320327494 @default.
• W3211465462 hasIssue "2" @default.
• W3211465462 hasLocation W32114654621 @default.
• W3211465462 hasLocation W32114654622 @default.

• next