Title |
Two fully automated data-driven 3D whole-breast segmentation strategies in MRI for MR-based breast density using image registration and U-Net with a focus on reproducibility
|
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Published in |
Visual Computing for Industry, Biomedicine, and Art, October 2022
|
DOI | 10.1186/s42492-022-00121-4 |
Pubmed ID | |
Authors |
Jia Ying, Renee Cattell, Tianyun Zhao, Lan Lei, Zhao Jiang, Shahid M. Hussain, Yi Gao, H.-H. Sherry Chow, Alison T. Stopeck, Patricia A. Thompson, Chuan Huang |
X Demographics
The data shown below were collected from the profiles of 4 X users 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 | 25% |
Netherlands | 1 | 25% |
Unknown | 2 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 3 | 75% |
Practitioners (doctors, other healthcare professionals) | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 16 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 4 | 25% |
Student > Ph. D. Student | 3 | 19% |
Professor | 2 | 13% |
Unspecified | 1 | 6% |
Unknown | 6 | 38% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 4 | 25% |
Business, Management and Accounting | 1 | 6% |
Unspecified | 1 | 6% |
Medicine and Dentistry | 1 | 6% |
Engineering | 1 | 6% |
Other | 0 | 0% |
Unknown | 8 | 50% |
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 14 October 2022.
All research outputs
#16,063,069
of 25,392,582 outputs
Outputs from Visual Computing for Industry, Biomedicine, and Art
#21
of 48 outputs
Outputs of similar age
#218,651
of 438,729 outputs
Outputs of similar age from Visual Computing for Industry, Biomedicine, and Art
#2
of 7 outputs
Altmetric has tracked 25,392,582 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 48 research outputs from this source. They receive a mean Attention Score of 2.9. This one scored the same or higher as 27 of them.
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 438,729 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 46th percentile – i.e., 46% 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 5 of them.