FluoRender: joint freehand segmentation and visualization for many-channel fluorescence data analysis
Abstract Background 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. Existing tools built on volume visualization pipelines for single channel or red-gr...
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| Format: | Article |
| Language: | English |
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BMC
2017-05-01
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| Series: | BMC Bioinformatics |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s12859-017-1694-9 |
| _version_ | 1811237133898219520 |
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| author | Yong Wan Hideo Otsuna Holly A. Holman Brig Bagley Masayoshi Ito A. Kelsey Lewis Mary Colasanto Gabrielle Kardon Kei Ito Charles Hansen |
| author_facet | Yong Wan Hideo Otsuna Holly A. Holman Brig Bagley Masayoshi Ito A. Kelsey Lewis Mary Colasanto Gabrielle Kardon Kei Ito Charles Hansen |
| author_sort | Yong Wan |
| collection | DOAJ |
| description | Abstract Background 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. 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. Results Here, 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. Conclusion The 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. |
| first_indexed | 2024-04-12T12:20:48Z |
| format | Article |
| id | doaj.art-376e602a74ae49958c0ecfc199f6d763 |
| institution | Directory Open Access Journal |
| issn | 1471-2105 |
| language | English |
| last_indexed | 2024-04-12T12:20:48Z |
| publishDate | 2017-05-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Bioinformatics |
| spelling | doaj.art-376e602a74ae49958c0ecfc199f6d7632022-12-22T03:33:18ZengBMCBMC Bioinformatics1471-21052017-05-0118111510.1186/s12859-017-1694-9FluoRender: joint freehand segmentation and visualization for many-channel fluorescence data analysisYong Wan0Hideo Otsuna1Holly A. Holman2Brig Bagley3Masayoshi Ito4A. Kelsey Lewis5Mary Colasanto6Gabrielle Kardon7Kei Ito8Charles Hansen9Scientific Computing and Imaging Institute, University of UtahJanelia Farm Research Campus, Howard Hughes Medical InstituteDepartment of Bioengineering, University of UtahScientific Computing and Imaging Institute, University of UtahInstitute of Molecular and Cellular Biosciences, University of TokyoDepartment of Biology, University of FloridaDepartment of Human Genetics, University of UtahDepartment of Human Genetics, University of UtahInstitute of Molecular and Cellular Biosciences, University of TokyoScientific Computing and Imaging Institute, University of UtahAbstract Background 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. 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. Results Here, 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. Conclusion The 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.http://link.springer.com/article/10.1186/s12859-017-1694-9MultichannelVolume dataVisualizationFreehand segmentationAnalysisGPUs |
| spellingShingle | Yong Wan Hideo Otsuna Holly A. Holman Brig Bagley Masayoshi Ito A. Kelsey Lewis Mary Colasanto Gabrielle Kardon Kei Ito Charles Hansen FluoRender: joint freehand segmentation and visualization for many-channel fluorescence data analysis BMC Bioinformatics Multichannel Volume data Visualization Freehand segmentation Analysis GPUs |
| title | FluoRender: joint freehand segmentation and visualization for many-channel fluorescence data analysis |
| title_full | FluoRender: joint freehand segmentation and visualization for many-channel fluorescence data analysis |
| title_fullStr | FluoRender: joint freehand segmentation and visualization for many-channel fluorescence data analysis |
| title_full_unstemmed | FluoRender: joint freehand segmentation and visualization for many-channel fluorescence data analysis |
| title_short | FluoRender: joint freehand segmentation and visualization for many-channel fluorescence data analysis |
| title_sort | fluorender joint freehand segmentation and visualization for many channel fluorescence data analysis |
| topic | Multichannel Volume data Visualization Freehand segmentation Analysis GPUs |
| url | http://link.springer.com/article/10.1186/s12859-017-1694-9 |
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