Abstract
BackgroundImage segmentation and registration techniques have enabled biologists to place large amounts of volume data from fluorescence microscopy, morphed three-dimensionally, onto a common spatial frame. Existing tools built on volume visualization pipelines for single channel or red-green-blue (RGB) channels have become inadequate for the new challenges of fluorescence microscopy. For a three-dimensional atlas of the insect nervous system, hundreds of volume channels are rendered simultaneously, whereas fluorescence intensity values from each channel need to be preserved for versatile adjustment and analysis. Although several existing tools have incorporated support of multichannel data using various strategies, the lack of a flexible design has made true many-channel visualization and analysis unavailable. The most common practice for many-channel volume data presentation is still converting and rendering pseudosurfaces, which are inaccurate for both qualitative and quantitative evaluations.ResultsHere, we present an alternative design strategy that accommodates the visualization and analysis of about 100 volume channels, each of which can be interactively adjusted, selected, and segmented using freehand tools. Our multichannel visualization includes a multilevel streaming pipeline plus a triple-buffer compositing technique. Our method also preserves original fluorescence intensity values on graphics hardware, a crucial feature that allows graphics-processing-unit (GPU)-based processing for interactive data analysis, such as freehand segmentation. We have implemented the design strategies as a thorough restructuring of our original tool, FluoRender.ConclusionThe redesign of FluoRender not only maintains the existing multichannel capabilities for a greatly extended number of volume channels, but also enables new analysis functions for many-channel data from emerging biomedical-imaging techniques.
Highlights
Image segmentation and registration techniques have enabled biologists to place large amounts of volume data from fluorescence microscopy, morphed three-dimensionally, onto a common spatial frame
1) The ideology allows an extended number of volume channels to be directly visualized in 3D. 2) It visualizes volume data based on the original intensity values of each channel, without the pseudosurface extraction that often yields a misleading appearance of a structure, and it supports a variety of visualization configurations
3) Data for visualization and analysis are readily shared on GPUs, ensuring that segmentation and analysis of multichannel data are based on the original intensity values of each channel
Summary
Image segmentation and registration techniques have enabled biologists to place large amounts of volume data from fluorescence microscopy, morphed three-dimensionally, onto a common spatial frame. Recent research on the insect nervous system has developed data processing techniques for image registration and segmentation, which enable us to place large amounts of volume data, morphed three-dimensionally, onto a common spatial frame, called a template, for visual examination and computational analysis [1, 2]. In such applications, several tens of independent three-dimensional (3D). Colocalization analysis and morphological comparison of several neural structures benefit from isolating these structures and cleaning up background signals; tracking 3D movements of cells often requires focusing on one or several subsets for detailed studies or troubleshooting issues from automatic algorithms
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