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Cortex Parcellation Associated Whole White Matter Parcellation in Individual Subjects

Overview of attention for article published in Frontiers in Human Neuroscience, July 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (74th percentile)
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

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Title
Cortex Parcellation Associated Whole White Matter Parcellation in Individual Subjects
Published in
Frontiers in Human Neuroscience, July 2017
DOI 10.3389/fnhum.2017.00352
Pubmed ID
Authors

Patrick Schiffler, Jan-Gerd Tenberge, Heinz Wiendl, Sven G. Meuth

Abstract

The investigation of specific white matter areas is a growing field in neurological research and is typically achieved through the use of atlases. However, the definition of anatomically based regions remains challenging for the white matter and thus hinders region-specific analysis in individual subjects. In this article, we focus on creating a whole white matter parcellation method for individual subjects where these areas can be associated to cortex regions. This is done by combining cortex parcellation and fiber tracking data. By tracking fibers out of each cortex region and labeling the fibers according to their origin, we populate a candidate image. We then derive the white matter parcellation by classifying each white matter voxel according to the distribution of labels in the corresponding voxel from the candidate image. The parcellation of the white matter with the presented method is highly reliable and is not as dependent on registration as with white matter atlases. This method allows for the parcellation of the whole white matter into individual cortex region associated areas and, therefore, associates white matter alterations to cortex regions. In addition, we compare the results from the presented method to existing atlases. The areas generated by the presented method are not as sharply defined as the areas in most existing atlases; however, they are computed directly in the DWI space of the subject and, therefore, do not suffer from distortion caused by registration. The presented approach might be a promising tool for clinical and basic research to investigate modalities or system specific micro structural alterations of white matter areas in a quantitative manner.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 49 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 11 22%
Student > Ph. D. Student 9 18%
Researcher 6 12%
Student > Doctoral Student 4 8%
Professor 3 6%
Other 7 14%
Unknown 9 18%
Readers by discipline Count As %
Neuroscience 13 27%
Computer Science 5 10%
Psychology 5 10%
Medicine and Dentistry 5 10%
Agricultural and Biological Sciences 4 8%
Other 6 12%
Unknown 11 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 01 August 2017.
All research outputs
#4,638,283
of 22,981,247 outputs
Outputs from Frontiers in Human Neuroscience
#2,085
of 7,182 outputs
Outputs of similar age
#81,151
of 313,502 outputs
Outputs of similar age from Frontiers in Human Neuroscience
#52
of 155 outputs
Altmetric has tracked 22,981,247 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,182 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.6. This one has gotten more attention than average, scoring higher than 70% of its peers.
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 313,502 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.
We're also able to compare this research output to 155 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.