High-Throughput Image Analysis of Lipid-Droplet-Bound Mitochondria.
Brown adipocyte morphology
Image analysis
Machine learning
Mitochondria
Journal
Methods in molecular biology (Clifton, N.J.)
ISSN: 1940-6029
Titre abrégé: Methods Mol Biol
Pays: United States
ID NLM: 9214969
Informations de publication
Date de publication:
2021
2021
Historique:
entrez:
1
6
2021
pubmed:
2
6
2021
medline:
9
7
2021
Statut:
ppublish
Résumé
Changes to mitochondrial architecture are associated with various adaptive and pathogenic processes. However, quantification of changes to mitochondrial structures is limited by the yet unmet challenge of defining the borders of each individual mitochondrion within an image. Here, we describe a novel method for segmenting primary brown adipocyte (BA) mitochondria images. We describe a granular approach to quantifying subcellular structures, particularly mitochondria in close proximity to lipid droplets: peridroplet mitochondria. In addition, we lay out a novel machine-learning-based mitochondrial segmentation method that eliminates the bias of manual mitochondrial segmentation and improves object recognition compared to conventional thresholding analyses. By applying these methods, we discovered a significant difference between cytosolic and peridroplet BA mitochondrial H
Identifiants
pubmed: 34060050
doi: 10.1007/978-1-0716-1266-8_22
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
285-303Références
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