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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A multi-institution evaluation of deformable image registration algorithms for automatic organ delineation in adaptive head and neck radiotherapy
|
|---|---|
| Published in |
Radiation Oncology, June 2012
|
| DOI | 10.1186/1748-717x-7-90 |
| Pubmed ID | |
| Authors |
Nicholas Hardcastle, Wolfgang A Tomé, Donald M Cannon, Charlotte L Brouwer, Paul WH Wittendorp, Nesrin Dogan, Matthias Guckenberger, Stéphane Allaire, Yogish Mallya, Prashant Kumar, Markus Oechsner, Anne Richter, Shiyu Song, Michael Myers, Bülent Polat, Karl Bzdusek |
| Abstract |
Adaptive Radiotherapy aims to identify anatomical deviations during a radiotherapy course and modify the treatment plan to maintain treatment objectives. This requires regions of interest (ROIs) to be defined using the most recent imaging data. This study investigates the clinical utility of using deformable image registration (DIR) to automatically propagate ROIs. |
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 % |
|---|---|---|
| Netherlands | 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 106 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 2 | 2% |
| Netherlands | 1 | <1% |
| United Kingdom | 1 | <1% |
| Austria | 1 | <1% |
| Denmark | 1 | <1% |
| Japan | 1 | <1% |
| Unknown | 99 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 29 | 27% |
| Student > Ph. D. Student | 21 | 20% |
| Student > Master | 10 | 9% |
| Other | 8 | 8% |
| Professor > Associate Professor | 6 | 6% |
| Other | 17 | 16% |
| Unknown | 15 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 36 | 34% |
| Physics and Astronomy | 26 | 25% |
| Engineering | 12 | 11% |
| Computer Science | 4 | 4% |
| Nursing and Health Professions | 4 | 4% |
| Other | 5 | 5% |
| Unknown | 19 | 18% |
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 26 July 2012.
All research outputs
#18,310,549
of 22,671,366 outputs
Outputs from Radiation Oncology
#1,407
of 2,044 outputs
Outputs of similar age
#127,851
of 166,057 outputs
Outputs of similar age from Radiation Oncology
#16
of 26 outputs
Altmetric has tracked 22,671,366 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 2,044 research outputs from this source. They receive a mean Attention Score of 2.7. This one is in the 18th percentile – i.e., 18% 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 166,057 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 26 others from the same source and published within six weeks on either side of this one. This one is in the 3rd percentile – i.e., 3% of its contemporaries scored the same or lower than it.