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3Dscript: animating 3D/4D microscopy data using a natural-language-based syntax

Nature Methods volume 16, pages 278–280 (2019)Cite this article

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3Dscript, an ImageJ/Fiji2,3 plugin, addresses the need for an intuitive way to assemble complex and high-quality animations. Here, animations are described by a list of instructions such as “From frame 0 to frame 180 rotate by 180 degrees horizontally ease-out” written in a syntax that is based on natural English language (Fig. 1b, Supplementary Notes). Each sentence starts with a frame interval that is followed by an action (e.g., “rotate,” “translate,” “zoom,” “change”) and the associated parameters. It ends optionally with an easing keyword (e.g., “linear,” “ease-in,” “ease-out,” “ease-in-out”) describing nonlinear motions often used in the animation of user interface elements in modern web design. 3Dscript provides instructions for spatially transforming an object in 3D; for animating 4D time-lapse data (Supplementary Video 2); and for changing rendering properties such as contrast, channel weights, clipping and so on (Supplementary Videos 3 and 4).

Unlike in key-frame-based animation, arbitrarily complex motions are intuitively implemented via the chaining of multiple instructions. Transformations, which are generally order dependent, are naturally applied in the order in which they appear in the text. Mixing of rotations and translations appropriately allows users, for example, to shift the center of rotation and generate planet-like motions, with an object rotating at the same time around both its own and an offset axis. Multiple instructions that apply in the same frame interval can be written concisely as enumerations (Fig. 1b).

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Fig. 1: Natural-language-based animation.

Code availability

The peer-reviewed version of the software is available as Supplementary Software. The source code is available at https://github.com/bene51/3Dscript, and binary releases for Windows, Linux and Mac OS X versions are available from our Fiji update site, https://romulus.oice.uni-erlangen.de/updatesite/. User documentation is available at https://bene51.github.io/3Dscript.

Data availability

All raw data used to create the figures and videos in this paper are available from the corresponding author upon reasonable request.

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Acknowledgements

We thank J. He and E. Haynes for the time-lapse image data of the zebrafish nervous system; A. Wandersee for the image data of the mouse organoid; D. Thieme for the image data of the human cornea; and A. Schmied and K. Enderle for extensive testing and feedback. This work was supported by DFG-CRC1181 Z02 (T.F.); DFG-CRC1181 C02 and DFG-FOR2438 P9 (C.K., A. Schmied and K. Enderle; awarded to C. Neufert, Med1, UK Erlangen); DFG-CRC1181 C05 and DFG-CRC796 B9 (A. Wandersee and B.R.; awarded to C. Becker, Med1, UK Erlangen); DFG-CRC1181 A02 (A.G.); and ERC-2014-CoG 647885 (SmartMic; J.H.).

Author information

Authors and Affiliations

  1. Optical Imaging Centre Erlangen, University of Erlangen-Nuremberg, Erlangen, Germany

    Benjamin Schmid, Philipp Tripal, Tina Fraaß & Ralf Palmisano

  2. Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany

    Benjamin Schmid & Jan Huisken

  3. Department of Medicine 1, University of Erlangen-Nuremberg, Erlangen, Germany

    Christina Kersten & Barbara Ruder

  4. Department of Medicine 3, University of Erlangen-Nuremberg, Erlangen, Germany

    Anika Grüneboom

  5. Morgridge Institute for Research, Madison, WI, USA

    Jan Huisken

  6. Department of Integrative Biology, University of Wisconsin, Madison, WI, USA

    Jan Huisken

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  1. Benjamin Schmid
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  2. Philipp Tripal
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  3. Tina Fraaß
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  4. Christina Kersten
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  7. Jan Huisken
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  8. Ralf Palmisano
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Contributions

B.S., R.P. and J.H. conceived the project. B.S. designed and implemented the software. C.K., B.R. and A.G. prepared samples and acquired imaging data. P.T. and T.F. tested the software on image data from multiple acquisition modalities. B.S., R.P. and J.H. wrote the manuscript. R.P. and J.H. supervised the project.

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Correspondence to Benjamin Schmid.

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The authors declare no competing interests.

Integrated supplementary information

Supplementary Figure 1 Screenshot of all software components.

Top: The ImageJ main window. Left: The animation editor, which is based on the Fiji Script Editor. Middle: The 3D window with the rendering output. Right: The control window for adjusting all possible settings of the integrated 3D renderer.

Supplementary Figure 2 Influence of non-linear gamma adjustment on the rendering output.

Leaf of A. thaliana, acquired with a Zeiss LSM880 NLO 2-photon microscope. All nine panels are rendered with identical settings for intensity and opacity minimum and maximum. Gamma for intensity increases from top to bottom (0.5, 1, 2), gamma for opacity increases from left to write (0.5, 1, 3). Scale bar: 50 µm..

Supplementary Figure 3 Comparison of different rendering algorithms.

From left to right: Independent transparency, combined transparency and maximum intensity projection rendering of colon tumors in an inflammation-related mouse colon cancer model. Images were acquired on a light sheet microscope after blood vessel staining (CD31; red) and ECi-based tissue clearing1. Gray: autofluorescence, scale bar: 500 µm.

Supplementary Figure 4 Using virtual lighting to emphasize surfaces.

Left: No lighting. Middle: ko = 0.7, kd = 0.3, ks = 0.2, s = 20. Right: ko = 0.4, kd = 0.5, ks = 0.3, s = 20. ko, kd, ks and s are the parameters of the Blinn-Phong shading model for the contributions of object light, diffuse light, specular light and shininess, respectively. No surfaces (e.g. in form of triangle meshes) were calculated. Example MRI dataset bundled with ImageJ, scale bar 20 mm.

Supplementary Figure 5 Extendibility of our framework.

In general, any third-party rendering software can integrate our text-based animation framework by implementing a couple of interfaces defined by our module. We have implemented modules that use POV-Ray (shown here) and the ImageJ 3D Viewer for rendering.

Supplementary information

Supplementary Information

Supplementary Figures 1–5 and Supplementary Notes 1–8

Reporting Summary

Supplementary Software

3Dscript—text-based animation.

Supplementary Video 1

Simultaneous rotation around multiple axes. 3D animation of mouse colon tumors using blood vessel staining (CD31, red), ECi-based tissue clearing and a LaVision BioTec lightsheet UltraMicroscope II (see also Fig. 1). The image volume is rotated around its y-axis (with a higher speed) and around the x-axis of the view (with a lower speed). Only a couple of text lines (Supplementary Notes, https://bene51.github.io/3Dscript/gallery.html) are required to describe an animation, which is hard to achieve with key frame-based animation. Scale bar, 500 μm.

Supplementary Video 2

Animated transformation through time. Animation of a growing zebrafish nervous system, imaged on a custom-built light-sheet microscope. While the time-lapse progresses, the image volume is spatially transformed. The animation text is available in the Supplementary Notes and at https://bene51.github.io/3Dscript/gallery.html. Scale bar, 100 μm.

Supplementary Video 3

Simultaneous pivoting and channel switching. Animation of a mouse paw, imaged on a LaVision BioTec light-sheet UltraMicroscope II. Pivoting is implemented with a macro. The animation text is available in the Supplementary Notes and at https://bene51.github.io/3Dscript/gallery.html. Scale bar, 500 μm.

Supplementary Video 4

Consecutive zoom-in and scroll-through at different positions. Animation of a mouse paw, imaged on a LaVision BioTec light-sheet UltraMicroscope II. The animation text is available in the Supplementary Notes and at https://bene51.github.io/3Dscript/gallery.html. Scale bar, 500 μm.

Supplementary Video 5

Macro for parameterized zooming. Animation of a human cornea imaged on a Zeiss LSM880 NLO two-photon microscope. The dataset is elongated in one dimension. Instead of zooming out during the entire animation, the zoom is adjusted to the rotation to always fill the available video canvas optimally, using a macro. The animation text is available in the Supplementary Notes and at https://bene51.github.io/3Dscript/gallery.html. Supplementary Video 6 and the Supplementary Notes describe in detail how this animation was created. Scale bar, 50 μm.

Supplementary Video 6

Composing an animation. This screencast demonstrates how the animation of the human cornea (Supplementary Video 5) is built up, and highlights the auto-completion features of the Animation Editor. A detailed step-by-step description also can be found in the Supplementary Notes.

Supplementary Video 7

Auto-completion. A dedicated animation editor, based on Fiji’s script editor, facilitates the composition of the animation description with auto-completion and recording capabilities.

Supplementary Video 8

The dedicated animation editor can record different rendering states and automatically create the description text to transition between them.

Supplementary Video 9

Rendering of an MRI image volume of a human head using the BigDataViewer. To demonstrate the extendibility of our framework, we wrote an adaptor for Fiji’s BigDataViewer. The animation text is available in the Supplementary Notes and at https://bene51.github.io/3Dscript/gallery.html.

Supplementary Video 10

Photo-realistic rendering of an organoid from the mouse intestine in a laboratory environment using POV-Ray. To demonstrate the extendibility of our framework, we wrote an adaptor that uses POV-Ray, a software for photorealistic rendering, instead of the integrated 3D renderer. The animation text is available in the Supplementary Notes and at https://bene51.github.io/3Dscript/gallery.html.

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Schmid, B., Tripal, P., Fraaß, T. et al. 3Dscript: animating 3D/4D microscopy data using a natural-language-based syntax. Nat Methods 16, 278–280 (2019). https://doi.org/10.1038/s41592-019-0359-1

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