You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Color edges extraction using statistical features and automatic threshold technique: application to the breast cancer cells
|
|---|---|
| Published in |
BioMedical Engineering OnLine, January 2014
|
| DOI | 10.1186/1475-925x-13-4 |
| Pubmed ID | |
| Authors |
Salim Ben Chaabane, Farhat Fnaiech |
| Abstract |
Color image segmentation has been so far applied in many areas; hence, recently many different techniques have been developed and proposed. In the medical imaging area, the image segmentation may be helpful to provide assistance to doctor in order to follow-up the disease of a certain patient from the breast cancer processed images. The main objective of this work is to rebuild and also to enhance each cell from the three component images provided by an input image. Indeed, from an initial segmentation obtained using the statistical features and histogram threshold techniques, the resulting segmentation may represent accurately the non complete and pasted cells and enhance them. This allows real help to doctors, and consequently, these cells become clear and easy to be counted. |
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 Kingdom | 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 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 8% |
| Unknown | 11 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 2 | 17% |
| Lecturer | 1 | 8% |
| Student > Doctoral Student | 1 | 8% |
| Other | 1 | 8% |
| Student > Ph. D. Student | 1 | 8% |
| Other | 3 | 25% |
| Unknown | 3 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 4 | 33% |
| Social Sciences | 2 | 17% |
| Physics and Astronomy | 1 | 8% |
| Computer Science | 1 | 8% |
| Medicine and Dentistry | 1 | 8% |
| Other | 1 | 8% |
| Unknown | 2 | 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 24 January 2014.
All research outputs
#22,756,649
of 25,371,288 outputs
Outputs from BioMedical Engineering OnLine
#733
of 867 outputs
Outputs of similar age
#281,155
of 320,688 outputs
Outputs of similar age from BioMedical Engineering OnLine
#12
of 18 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 867 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one is in the 1st percentile – i.e., 1% 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 320,688 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
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 is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.