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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Maximizing Kolmogorov Complexity for accurate and robust bright field cell segmentation
|
|---|---|
| Published in |
BMC Bioinformatics, January 2014
|
| DOI | 10.1186/1471-2105-15-32 |
| Pubmed ID | |
| Authors |
Hamid Mohamadlou, Joseph C Shope, Nicholas S Flann |
| Abstract |
Analysis of cellular processes with microscopic bright field defocused imaging has the advantage of low phototoxicity and minimal sample preparation. However bright field images lack the contrast and nuclei reporting available with florescent approaches and therefore present a challenge to methods that segment and track the live cells. Moreover, such methods must be robust to systemic and random noise, variability in experimental configuration, and the multiple unknowns in the biological system under study. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Norway | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 17% |
| Unknown | 5 | 83% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 3 | 50% |
| Professor | 1 | 17% |
| Student > Ph. D. Student | 1 | 17% |
| Other | 1 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 2 | 33% |
| Agricultural and Biological Sciences | 2 | 33% |
| Medicine and Dentistry | 1 | 17% |
| Design | 1 | 17% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 04 April 2015.
All research outputs
#14,772,245
of 22,741,406 outputs
Outputs from BMC Bioinformatics
#5,039
of 7,267 outputs
Outputs of similar age
#182,681
of 307,435 outputs
Outputs of similar age from BMC Bioinformatics
#60
of 96 outputs
Altmetric has tracked 22,741,406 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,267 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 26th percentile – i.e., 26% of its peers scored the same or lower than it.
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 307,435 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 96 others from the same source and published within six weeks on either side of this one. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.