| Title |
Workflow for Visualization of Neuroimaging Data with an Augmented Reality Device
|
|---|---|
| Published in |
Journal of Digital Imaging, July 2017
|
| DOI | 10.1007/s10278-017-9991-4 |
| Pubmed ID | |
| Authors |
Christof Karmonik, Timothy B. Boone, Rose Khavari |
| Abstract |
Commercial availability of three-dimensional (3D) augmented reality (AR) devices has increased interest in using this novel technology for visualizing neuroimaging data. Here, a technical workflow and algorithm for importing 3D surface-based segmentations derived from magnetic resonance imaging data into a head-mounted AR device is presented and illustrated on selected examples: the pial cortical surface of the human brain, fMRI BOLD maps, reconstructed white matter tracts, and a brain network of functional connectivity. |
X Demographics
The data shown below were collected from the profiles of 176 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 41 | 23% |
| United Kingdom | 28 | 16% |
| Netherlands | 7 | 4% |
| France | 6 | 3% |
| Ireland | 4 | 2% |
| Germany | 3 | 2% |
| Chile | 3 | 2% |
| Canada | 3 | 2% |
| Australia | 2 | 1% |
| Other | 22 | 13% |
| Unknown | 57 | 32% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 92 | 52% |
| Scientists | 70 | 40% |
| Practitioners (doctors, other healthcare professionals) | 10 | 6% |
| Science communicators (journalists, bloggers, editors) | 4 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 53 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 8 | 15% |
| Researcher | 8 | 15% |
| Student > Master | 7 | 13% |
| Other | 3 | 6% |
| Professor > Associate Professor | 3 | 6% |
| Other | 14 | 26% |
| Unknown | 10 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 8 | 15% |
| Engineering | 7 | 13% |
| Computer Science | 6 | 11% |
| Agricultural and Biological Sciences | 3 | 6% |
| Biochemistry, Genetics and Molecular Biology | 3 | 6% |
| Other | 11 | 21% |
| Unknown | 15 | 28% |
Attention Score in Context
This research output has an Altmetric Attention Score of 109. 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 20 March 2022.
All research outputs
#393,727
of 25,750,437 outputs
Outputs from Journal of Digital Imaging
#3
of 986 outputs
Outputs of similar age
#8,192
of 326,991 outputs
Outputs of similar age from Journal of Digital Imaging
#1
of 29 outputs
Altmetric has tracked 25,750,437 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 986 research outputs from this source. They receive a mean Attention Score of 4.9. This one has done particularly well, scoring higher than 99% 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 326,991 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 97% of its contemporaries.
We're also able to compare this research output to 29 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.