https://www.selleckchem.com/products/asp5878.html
cribe how the logical organization of biological facts in the form of an ontology can provide useful constraints that facilitate automatic processing of complex images. We demonstrate the results of ontology-guided segmentation and object identification in mouse developmental lung images from the Bioinformatics REsource ATlas for the Healthy lung database of the Molecular Atlas of Lung Development (LungMAP1) program CONCLUSION We describe a novel ontology-guided approach to segmentation and classification of complex immunofluorescence i
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