Ontology-guided segmentation and object identification for developmental mouse lung immunofluorescent images

Ontology-guided segmentation and object identification for developmental mouse lung immunofluorescent images

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Background: Immunofluorescent confocal microscopy uses labeled antibodies as probes against specific macromolecules to discriminate between multiple cell types. For images of the developmental mouse lung, these cells are themselves organized into densely packed higher-level anatomical structures. Th...

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Bibliographic Details
Main Authors: Ardini-Polaske, M. (Author), Aronow, B. (Author), Chan, C. (Author), Gaddis, N. (Author), Hill, C.B (Author), LungMAP Consortium (Author), Masci, A.M (Author), Misra, R.S (Author), Neely, B. (Author), Palmer, S.M (Author), Wert, S.E (Author), White, S. (Author), Yang, L. (Author)
Format: Article
Language:English
Published: BioMed Central Ltd 2021
Subjects:
algorithm
Algorithms
Anatomical structures
animal
animal experiment
Animals
article
bioinformatics
Bioinformatics resources
Biological organs
Biology
Classification (of information)
Computer aided diagnosis
confocal microscopy
Contextual information
diagnostic imaging
fluorescent antibody technique
Fluorescent Antibody Technique
Histological structure
histopathology
image analysis
Image analysis
Image classification
image processing
Image processing
Image Processing, Computer-Assisted
image segmentation
Image segmentation
immunofluorescence
Immunofluorescent images
Innovative approaches
Labeled training data
lung
Lung
lung development
machine learning
Machine learning
male
metadata
Mice
Microscopy, Confocal
mouse
nonhuman
Object identification
ontology
Ontology
Probes
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