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Mathematical morphology-based approach to the enhancement of morphological features in medical images

Overview of attention for article published in Journal of Clinical Bioinformatics, January 2011
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Mentioned by

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1 tweeter

Citations

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39 Dimensions

Readers on

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42 Mendeley
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Title
Mathematical morphology-based approach to the enhancement of morphological features in medical images
Published in
Journal of Clinical Bioinformatics, January 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.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 42 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 40 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 31%
Student > Master 6 14%
Student > Bachelor 4 10%
Student > Doctoral Student 3 7%
Researcher 3 7%
Other 6 14%
Unknown 7 17%
Readers by discipline Count As %
Engineering 8 19%
Computer Science 6 14%
Medicine and Dentistry 4 10%
Agricultural and Biological Sciences 4 10%
Physics and Astronomy 3 7%
Other 8 19%
Unknown 9 21%

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
#10,046,939
of 12,558,412 outputs
Outputs from Journal of Clinical Bioinformatics
#42
of 60 outputs
Outputs of similar age
#151,994
of 211,804 outputs
Outputs of similar age from Journal of Clinical Bioinformatics
#10
of 15 outputs
Altmetric has tracked 12,558,412 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 60 research outputs from this source. They receive a mean Attention Score of 2.5. This one is in the 5th percentile – i.e., 5% 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 211,804 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 15 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.