A high-level 3D visualization API for Java and ImageJ

By Benjamin Schmid, Johannes E. Schindelin, Albert Cardona, Mark Longair, Martin Heisenberg. 2010

546 citations recorded by the source corpus.

BackgroundCurrent imaging methods such as Magnetic Resonance Imaging (MRI), Confocal microscopy, Electron Microscopy (EM) or Selective Plane Illumination Microscopy (SPIM) yield three-dimensional (3D) data sets in need of appropriate computational methods for their analysis. The reconstruction, segmentation and registration are best approached from the 3D representation of the data set.ResultsHere we present a platform-independent framework based on Java and Java 3D for accelerated rendering of biological images. Our framework is seamlessly integrated into ImageJ, a free image processing package with a vast collection of community-developed biological image analysis tools. Our framework enriches the ImageJ software libraries with methods that greatly reduce the complexity of developing image analysis tools in an interactive 3D visualization environment. In particular, we provide high-level access to volume rendering, volume editing, surface extraction, and image annotation. The ability to rely on a library that removes the low-level details enables concentrating software development efforts on the algorithm implementation parts.ConclusionsOur framework enables biomedical image software development to be built with 3D visualization capabilities with very little effort. We offer the source code and convenient binary packages along with extensive documentation at http://3dviewer.neurofly.de.

Subfields: Biophysics, Computer Vision and Pattern Recognition, Structural Biology, Human-Computer Interaction

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Citations in the corpus

An Integrated Micro- and Macroarchitectural Analysis of the Drosophila Brain by Computer-Assisted Serial Section Electron Microscopy (2010, methodology): “. Both image volumes and segmented objects may be visualized in 3D for spatial analysis, using the ImageJ “3D Viewer””
Fiji - an Open Source platform for biological image analysis (2012, methodology): “3o ) and the tracking of nuclei across time ( Supplementary Video 4 ) can be visualized using the Fiji 4D Viewer 25 .”
BoneJ: free and extensible bone image analysis in ImageJ (2010, methodology): “BoneJ makes use of the ImageJ 3D Viewer [34], which provides hardware-accelerated visualisation of 3D and 4D (3D × time) multichannel data.”
The ImageJ ecosystem: an open platform for biomedical image analysis (2015, methodology): “Over time, projects such as the 3D Viewer, the Simple Neurite Tracer, and bUnwarpJ (Arganda!”
Effects of vegetation restoration on soil aggregate microstructure quantified with synchrotron-based micro-computed tomography (2012, methodology): “Volume rendering and visualization of the 3D aggregates were established with the ImageJ 3D viewer plugin (Schmid et al., 2010) and examples are shown in Fig.”
The ImageJ ecosystem: Open‐source software for image visualization, processing, and analysis (2020, background): “37,73 Recent updates include support for registering 4D or 5D multichannel or multitime images, and future efforts will include new transformation models, as well as extended support for images where intensity may be modulated upon adjusting size.”
Microscopy Image Browser: A Platform for Segmentation and Analysis of Multidimensional Datasets (2016, methodology): “FromMIB, the results of the segmentation (models) can be directly visualized using MATLAB engine (Fig 2A), Fiji 3-D viewer [33,34], and Imaris or saved in formats that are compatible with other visualization programs, i.”
TrackMate: An open and extensible platform for single-particle tracking. (2017, methodology): “2, bottom left), based on the ImageJ 3D viewer [16].”