Orbit Image Analysis: An open-source whole slide image analysis tool

PLoS Comput Biol. 2020 Feb 5;16(2):e1007313. doi: 10.1371/journal.pcbi.1007313. eCollection 2020 Feb.


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.

MeSH terms

  • Algorithms
  • Deep Learning
  • Humans
  • Image Processing, Computer-Assisted / methods
  • Orbit / anatomy & histology*
  • User-Computer Interface

Associated data

  • Dryad/10.5061/dryad.fqz612jpc

Grant support

The authors received no specific funding for this work.