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X Demographics
Mendeley readers
Attention Score in Context
| Title |
FluoRender: joint freehand segmentation and visualization for many-channel fluorescence data analysis
|
|---|---|
| Published in |
BMC Bioinformatics, May 2017
|
| DOI | 10.1186/s12859-017-1694-9 |
| Pubmed ID | |
| Authors |
Yong Wan, Hideo Otsuna, Holly A. Holman, Brig Bagley, Masayoshi Ito, A. Kelsey Lewis, Mary Colasanto, Gabrielle Kardon, Kei Ito, Charles Hansen |
| Abstract |
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. 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. 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. |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 17% |
| Canada | 1 | 17% |
| Australia | 1 | 17% |
| France | 1 | 17% |
| United States | 1 | 17% |
| Unknown | 1 | 17% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 67% |
| Scientists | 2 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 39 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 8 | 21% |
| Researcher | 8 | 21% |
| Student > Bachelor | 2 | 5% |
| Professor | 2 | 5% |
| Student > Postgraduate | 2 | 5% |
| Other | 6 | 15% |
| Unknown | 11 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 6 | 15% |
| Biochemistry, Genetics and Molecular Biology | 5 | 13% |
| Agricultural and Biological Sciences | 5 | 13% |
| Neuroscience | 4 | 10% |
| Medicine and Dentistry | 3 | 8% |
| Other | 4 | 10% |
| Unknown | 12 | 31% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 June 2019.
All research outputs
#7,282,428
of 22,977,819 outputs
Outputs from BMC Bioinformatics
#2,874
of 7,308 outputs
Outputs of similar age
#115,425
of 313,455 outputs
Outputs of similar age from BMC Bioinformatics
#43
of 108 outputs
Altmetric has tracked 22,977,819 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 7,308 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has gotten more attention than average, scoring higher than 59% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 313,455 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 62% of its contemporaries.
We're also able to compare this research output to 108 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 58% of its contemporaries.