Orbit Image Analysis: An open-source whole slide image analysis tool.
Journal
PLoS computational biology
ISSN: 1553-7358
Titre abrégé: PLoS Comput Biol
Pays: United States
ID NLM: 101238922
Informations de publication
Date de publication:
02 2020
02 2020
Historique:
received:
07
08
2019
accepted:
11
12
2019
revised:
18
02
2020
pubmed:
6
2
2020
medline:
28
5
2020
entrez:
6
2
2020
Statut:
epublish
Résumé
We describe Orbit Image Analysis, an open-source whole slide image analysis tool. The tool consists of a generic tile-processing engine which allows the execution of various image analysis algorithms provided by either Orbit itself or from other open-source platforms using a tile-based map-reduce execution framework. Orbit Image Analysis is capable of sophisticated whole slide imaging analyses due to several key features. First, Orbit has machine-learning capabilities. This deep learning segmentation can be integrated with complex object detection for analysis of intricate tissues. In addition, Orbit can run locally as standalone or connect to the open-source image server OMERO. Another important characteristic is its scale-out functionality, using the Apache Spark framework for distributed computing. In this paper, we describe the use of Orbit in three different real-world applications: quantification of idiopathic lung fibrosis, nerve fibre density quantification, and glomeruli detection in the kidney.
Identifiants
pubmed: 32023239
doi: 10.1371/journal.pcbi.1007313
pii: PCOMPBIOL-D-19-01147
pmc: PMC7028292
doi:
Banques de données
Dryad
['10.5061/dryad.fqz612jpc']
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
e1007313Déclaration de conflit d'intérêts
The authors are paid for their work by Idorsia Pharmaceuticals Ltd.
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