Literature DB >> 33976878

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

Romain Guiet1, Olivier Burri1, Nicolas Chiaruttini1, Olivier Hagens2, Arne Seitz1.   

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. Copyright:
© 2021 Guiet R et al.

Entities:  

Keywords:  BigDataViewer; Image Processing; ImageJ/Fiji; Large datasets; Light-sheet fluorescence microscopy

Mesh:

Year:  2020        PMID: 33976878      PMCID: PMC8097733          DOI: 10.12688/f1000research.25447.2

Source DB:  PubMed          Journal:  F1000Res        ISSN: 2046-1402


  6 in total

1.  BigDataViewer: visualization and processing for large image data sets.

Authors:  Tobias Pietzsch; Stephan Saalfeld; Stephan Preibisch; Pavel Tomancak
Journal:  Nat Methods       Date:  2015-06       Impact factor: 28.547

2.  Fiji: an open-source platform for biological-image analysis.

Authors:  Johannes Schindelin; Ignacio Arganda-Carreras; Erwin Frise; Verena Kaynig; Mark Longair; Tobias Pietzsch; Stephan Preibisch; Curtis Rueden; Stephan Saalfeld; Benjamin Schmid; Jean-Yves Tinevez; Daniel James White; Volker Hartenstein; Kevin Eliceiri; Pavel Tomancak; Albert Cardona
Journal:  Nat Methods       Date:  2012-06-28       Impact factor: 28.547

3.  BigStitcher: reconstructing high-resolution image datasets of cleared and expanded samples.

Authors:  David Hörl; Fabio Rojas Rusak; Friedrich Preusser; Paul Tillberg; Nadine Randel; Raghav K Chhetri; Albert Cardona; Philipp J Keller; Hartmann Harz; Heinrich Leonhardt; Mathias Treier; Stephan Preibisch
Journal:  Nat Methods       Date:  2019-08-05       Impact factor: 28.547

4.  ACT-PRESTO: Rapid and consistent tissue clearing and labeling method for 3-dimensional (3D) imaging.

Authors:  Eunsoo Lee; Jungyoon Choi; Youhwa Jo; Joo Yeon Kim; Yu Jin Jang; Hye Myeong Lee; So Yeun Kim; Ho-Jae Lee; Keunchang Cho; Neoncheol Jung; Eun Mi Hur; Sung Jin Jeong; Cheil Moon; Youngshik Choe; Im Joo Rhyu; Hyun Kim; Woong Sun
Journal:  Sci Rep       Date:  2016-01-11       Impact factor: 4.379

5.  Engineered AAVs for efficient noninvasive gene delivery to the central and peripheral nervous systems.

Authors:  Ken Y Chan; Min J Jang; Bryan B Yoo; Alon Greenbaum; Namita Ravi; Wei-Li Wu; Luis Sánchez-Guardado; Carlos Lois; Sarkis K Mazmanian; Benjamin E Deverman; Viviana Gradinaru
Journal:  Nat Neurosci       Date:  2017-06-26       Impact factor: 24.884

6.  The mesoSPIM initiative: open-source light-sheet microscopes for imaging cleared tissue.

Authors:  Fabian F Voigt; Daniel Kirschenbaum; Evgenia Platonova; Stéphane Pagès; Robert A A Campbell; Rahel Kastli; Martina Schaettin; Ladan Egolf; Alexander van der Bourg; Philipp Bethge; Karen Haenraets; Noémie Frézel; Thomas Topilko; Paola Perin; Daniel Hillier; Sven Hildebrand; Anna Schueth; Alard Roebroeck; Botond Roska; Esther T Stoeckli; Roberto Pizzala; Nicolas Renier; Hanns Ulrich Zeilhofer; Theofanis Karayannis; Urs Ziegler; Laura Batti; Anthony Holtmaat; Christian Lüscher; Adriano Aguzzi; Fritjof Helmchen
Journal:  Nat Methods       Date:  2019-09-16       Impact factor: 28.547

  6 in total

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