Journal of MicroscopyBioinformaticsPeer-reviewed journal article
ModularImageAnalysis (MIA): Assembly of modularised image and object analysis workflows in ImageJ
Abstract
ModularImageAnalysis (MIA) is an ImageJ plugin providing a code-free graphical environment in which complex automated analysis workflows can be constructed and distributed. The near 200 included modules cover all stages of a typical analysis workflow, from image loading through image processing, object detection, extraction of measurements, measurement-based filtering, visualisation, and data exporting. MIA provides out-of-the-box compatibility with many advanced image processing plugins for ImageJ including Bio-Formats, DeepImageJ, MorphoLibJ and TrackMate, allowing these tools and their outputs to be directly incorporated into analysis workflows. By default, modules support spatially calibrated 5D images, meaning measurements can be acquired in both pixel and calibrated units. A hierarchical object relationship model allows for both parent-child (one-to-many) and partner (many-to-many) relationships to be established. These relationships underpin MIAs ability to track objects through time, represent complex spatial relationships (e.g. skeletons) and measure object distributions (e.g. count puncta per cell). MIA features dual graphical interfaces: the "editing view" offers access to the full list of modules and parameters in the workflow, while the simplified "processing view" can be configured to display only a focused subset of controls. All workflows are batch-enabled by default, with image files within a specified folder being processed automatically and exported to a single spreadsheet. Beyond the included modules, functionality can be extended both internally, through integration with the ImageJ scripting interface, and externally, by developing third-party Java modules that extend the core MIA framework. Here we describe the design and functionality of MIA in the context of a series of real-world example analyses.
- assay: imaging
- research focus: software / tool
- research focus: benchmarking
- approach: experimental assay
- Citations
- 28
- FWCI
- 3.39
- Field percentile
- top 6%
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