| Title |
TReMAP: Automatic 3D Neuron Reconstruction Based on Tracing, Reverse Mapping and Assembling of 2D Projections
|
|---|---|
| Published in |
Neuroinformatics, August 2015
|
| DOI | 10.1007/s12021-015-9278-1 |
| Pubmed ID | |
| Authors |
Zhi Zhou, Xiaoxiao Liu, Brian Long, Hanchuan Peng |
| Abstract |
Efficient and accurate digital reconstruction of neurons from large-scale 3D microscopic images remains a challenge in neuroscience. We propose a new automatic 3D neuron reconstruction algorithm, TReMAP, which utilizes 3D Virtual Finger (a reverse-mapping technique) to detect 3D neuron structures based on tracing results on 2D projection planes. Our fully automatic tracing strategy achieves close performance with the state-of-the-art neuron tracing algorithms, with the crucial advantage of efficient computation (much less memory consumption and parallel computation) for large-scale images. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 70 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 2 | 3% |
| Unknown | 68 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 17 | 24% |
| Researcher | 14 | 20% |
| Student > Master | 10 | 14% |
| Other | 7 | 10% |
| Student > Doctoral Student | 4 | 6% |
| Other | 8 | 11% |
| Unknown | 10 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 18 | 26% |
| Engineering | 13 | 19% |
| Computer Science | 12 | 17% |
| Agricultural and Biological Sciences | 8 | 11% |
| Medicine and Dentistry | 3 | 4% |
| Other | 4 | 6% |
| Unknown | 12 | 17% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 08 September 2015.
All research outputs
#18,425,370
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Outputs from Neuroinformatics
#325
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Outputs of similar age
#193,045
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Outputs of similar age from Neuroinformatics
#5
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