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X Demographics
Mendeley readers
Attention Score in Context
| Title |
ATPP: A Pipeline for Automatic Tractography-Based Brain Parcellation
|
|---|---|
| Published in |
Frontiers in Neuroinformatics, May 2017
|
| DOI | 10.3389/fninf.2017.00035 |
| Pubmed ID | |
| Authors |
Hai Li, Lingzhong Fan, Junjie Zhuo, Jiaojian Wang, Yu Zhang, Zhengyi Yang, Tianzi Jiang |
| Abstract |
There is a longstanding effort to parcellate brain into areas based on micro-structural, macro-structural, or connectional features, forming various brain atlases. Among them, connectivity-based parcellation gains much emphasis, especially with the considerable progress of multimodal magnetic resonance imaging in the past two decades. The Brainnetome Atlas published recently is such an atlas that follows the framework of connectivity-based parcellation. However, in the construction of the atlas, the deluge of high resolution multimodal MRI data and time-consuming computation poses challenges and there is still short of publically available tools dedicated to parcellation. In this paper, we present an integrated open source pipeline (https://www.nitrc.org/projects/atpp), named Automatic Tractography-based Parcellation Pipeline (ATPP) to realize the framework of parcellation with automatic processing and massive parallel computing. ATPP is developed to have a powerful and flexible command line version, taking multiple regions of interest as input, as well as a user-friendly graphical user interface version for parcellating single region of interest. We demonstrate the two versions by parcellating two brain regions, left precentral gyrus and middle frontal gyrus, on two independent datasets. In addition, ATPP has been successfully utilized and fully validated in a variety of brain regions and the human Brainnetome Atlas, showing the capacity to greatly facilitate brain parcellation. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 30% |
| France | 2 | 20% |
| Switzerland | 1 | 10% |
| Australia | 1 | 10% |
| United Kingdom | 1 | 10% |
| China | 1 | 10% |
| Unknown | 1 | 10% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 8 | 80% |
| Scientists | 2 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 46 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 11 | 24% |
| Researcher | 6 | 13% |
| Professor > Associate Professor | 5 | 11% |
| Student > Master | 5 | 11% |
| Student > Doctoral Student | 3 | 7% |
| Other | 7 | 15% |
| Unknown | 9 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 16 | 35% |
| Engineering | 4 | 9% |
| Computer Science | 3 | 7% |
| Psychology | 3 | 7% |
| Medicine and Dentistry | 3 | 7% |
| Other | 3 | 7% |
| Unknown | 14 | 30% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 15 June 2017.
All research outputs
#6,736,385
of 25,382,250 outputs
Outputs from Frontiers in Neuroinformatics
#293
of 828 outputs
Outputs of similar age
#97,200
of 319,591 outputs
Outputs of similar age from Frontiers in Neuroinformatics
#3
of 18 outputs
Altmetric has tracked 25,382,250 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 828 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.8. This one has gotten more attention than average, scoring higher than 64% 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 319,591 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 69% of its contemporaries.
We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.