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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Mathematical morphology-based approach to the enhancement of morphological features in medical images
|
|---|---|
| Published in |
Journal of Clinical Bioinformatics, December 2011
|
| DOI | 10.1186/2043-9113-1-33 |
| Pubmed ID | |
| Authors |
Yoshitaka Kimori |
| Abstract |
Medical image processing is essential in many fields of medical research and clinical practice because it greatly facilitates early and accurate detection and diagnosis of diseases. In particular, contrast enhancement is important for optimal image quality and visibility. This paper proposes a new image processing method for enhancing morphological features of masses and other abnormalities in medical 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 % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 2% |
| Brazil | 1 | 2% |
| Unknown | 48 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 14 | 28% |
| Student > Master | 7 | 14% |
| Student > Bachelor | 4 | 8% |
| Student > Doctoral Student | 3 | 6% |
| Researcher | 3 | 6% |
| Other | 8 | 16% |
| Unknown | 11 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 11 | 22% |
| Computer Science | 7 | 14% |
| Medicine and Dentistry | 5 | 10% |
| Agricultural and Biological Sciences | 5 | 10% |
| Physics and Astronomy | 3 | 6% |
| Other | 6 | 12% |
| Unknown | 13 | 26% |
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 16 December 2011.
All research outputs
#20,653,708
of 25,371,288 outputs
Outputs from Journal of Clinical Bioinformatics
#44
of 61 outputs
Outputs of similar age
#203,430
of 247,992 outputs
Outputs of similar age from Journal of Clinical Bioinformatics
#4
of 7 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 61 research outputs from this source. They receive a mean Attention Score of 3.1. This one is in the 3rd percentile – i.e., 3% 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 247,992 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.