SciJava Interface for Parallel Execution in the ImageJ Ecosystem

Krumnikl, Michal; Bainar, Petr; Klímová, Jana; Kožusznik, Jan; Moravec, Pavel; Svaton, Vaclav; Tomančák, Pavel

doi:10.1007/978-3-319-99954-8_25

Cited by 2 publications

(1 citation statement)

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“…They can be invoked from other SciJava‐compatible applications including KNIME Analytics Platform, CellProfiler, OMERO, and others, as well as from user scripts, including for executing in headless mode from the command line, without any graphical user interface (Allan et al., 2012; Dietz et al., 2020; Kamentsky et al., 2011; Möller et al., 2016; Ouyang, Mueller, Hjelmare, Lundberg, & Zimmer, 2019). This is useful in several scenarios, including: for batch analysis across large quantities of data; when combining ImageJ functionality with other systems via standard interprocess interoperability approaches (files and/or pipes); for use within modules of container‐based workflow systems; and for distributed execution of analysis pipelines on server clusters (Krumnikl et al., 2018; Rubens et al., 2020; also see Apeer website in Internet Resources). See Support Protocol 2 for an example of invoking ImageJ headless from the command line.…”

Section: Commentarymentioning

confidence: 99%

New Extensibility and Scripting Tools in the ImageJ Ecosystem

et al. 2021

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ImageJ provides a framework for image processing across scientific domains while being fully open source. Over the years ImageJ has been substantially extended to support novel applications in scientific imaging as they emerge, particularly in the area of biological microscopy, with functionality made more accessible via the Fiji distribution of ImageJ. Within this software ecosystem, work has been done to extend the accessibility of ImageJ to utilize scripting, macros, and plugins in a variety of programming scenarios, e.g., from Groovy and Python and in Jupyter notebooks and cloud computing. We provide five protocols that demonstrate the extensibility of ImageJ for various workflows in image processing. We focus first on Fluorescence Lifetime Imaging Microscopy (FLIM) data, since this requires significant processing to provide quantitative insights into the microenvironments of cells. Second, we show how ImageJ can now be utilized for common image processing techniques, specifically image deconvolution and inversion, while highlighting the new, built‐in features of ImageJ—particularly its capacity to run completely headless and the Ops matching feature that selects the optimal algorithm for a given function and data input, thereby enabling processing speedup. Collectively, these protocols can be used as a basis for automating biological image processing workflows. © 2021 Wiley Periodicals LLC. Basic Protocol 1: Using PyImageJ for FLIM data processing Alternate Protocol: Groovy FLIMJ in Jupyter Notebooks Basic Protocol 2: Using ImageJ Ops for image deconvolution Support Protocol 1: Using ImageJ Ops matching feature for image inversion Support Protocol 2: Headless ImageJ deconvolution

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Section: Commentarymentioning

confidence: 99%

New Extensibility and Scripting Tools in the ImageJ Ecosystem

et al. 2021

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The study of capillarity phenomena by means of ImageJ software

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POPESCU

et al. 2023

Rom. Rep. Phys.

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"Capillarity phenomena appear due to different molecular forces acting between fluid molecules located at the interface with either another fluid or a solid. The macroscopic description of the phenomenon can be done in terms of surface tension. In this paper, we determined the surface tension coefficient of aqueous solution of potassium permanganate by means of Jurin's law and also made diameter measurements and capillary ascents on images by using ImageJ software. Furthermore, we studied the capillary phenomena between two parallel and non- parallel plates. In the case of non-parallel plates, employing a special plugin of the ImageJ software, we determined the equation of the rectangular hyperbola drawn by the surface of liquid rising between plates. These experiments can be performed at elementary level and, additionally, used as a stimulus to discover more advanced topics."

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SciJava Interface for Parallel Execution in the ImageJ Ecosystem

Cited by 2 publications

References 18 publications

New Extensibility and Scripting Tools in the ImageJ Ecosystem

New Extensibility and Scripting Tools in the ImageJ Ecosystem

The study of capillarity phenomena by means of ImageJ software

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