DEVILS: a tool for the visualization of large datasets with a high dynamic range.

F1000Res

BioImaging & Optics platform (BIOP), Faculty of Life Sciences (SV), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.

Published: May 2021

AI Article Synopsis

  • The dynamic range of image-based sensors exceeds what monitors can display, complicating visualization of images with both small and large intensity structures.
  • An ImageJ plugin called DEVILS has been developed to enhance the visualization of features by compressing intensity ranges, making subtle and bright details visible at the same time.
  • The plugin simplifies the process for users with an intuitive parameter, includes a preview mode, and allows for efficient processing of large datasets, ultimately creating outputs compatible with fast viewing tools like BigDataViewer.

Article Abstract

The number of grey values that can be displayed on monitors and be processed by the human eye is smaller than the dynamic range of image-based sensors. This makes the visualization of such data a challenge, especially with specimens where small dim structures are equally important as large bright ones, or whenever variations in intensity, such as non-homogeneous staining efficiencies or light depth penetration, becomes an issue. While simple intensity display mappings are easily possible, these fail to provide a one-shot observation that can display objects of varying intensities. In order to facilitate the visualization-based analysis of large volumetric datasets, we developed an easy-to-use ImageJ plugin enabling the compressed display of features within several magnitudes of intensities. The Display Enhancement for Visual Inspection of Large Stacks plugin (DEVILS) homogenizes the intensities by using a combination of local and global pixel operations to allow for high and low intensities to be visible simultaneously to the human eye. The plugin is based on a single, intuitively understandable parameter, features a preview mode, and uses parallelization to process multiple image planes. As output, the plugin is capable of producing a BigDataViewer-compatible dataset for fast visualization. We demonstrate the utility of the plugin for large volumetric image data.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8097733PMC
http://dx.doi.org/10.12688/f1000research.25447.2DOI Listing

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