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Acoustic window planning for ultrasound acquisition

Overview of attention for article published in International Journal of Computer Assisted Radiology and Surgery, March 2017
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (64th percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

Mentioned by

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1 X user
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1 Wikipedia page

Citations

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14 Dimensions

Readers on

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36 Mendeley
Title
Acoustic window planning for ultrasound acquisition
Published in
International Journal of Computer Assisted Radiology and Surgery, March 2017
DOI 10.1007/s11548-017-1551-3
Pubmed ID
Authors

Rüdiger Göbl, Salvatore Virga, Julia Rackerseder, Benjamin Frisch, Nassir Navab, Christoph Hennersperger

Abstract

Autonomous robotic ultrasound has recently gained considerable interest, especially for collaborative applications. Existing methods for acquisition trajectory planning are solely based on geometrical considerations, such as the pose of the transducer with respect to the patient surface. This work aims at establishing acoustic window planning to enable autonomous ultrasound acquisitions of anatomies with restricted acoustic windows, such as the liver or the heart. We propose a fully automatic approach for the planning of acquisition trajectories, which only requires information about the target region as well as existing tomographic imaging data, such as X-ray computed tomography. The framework integrates both geometrical and physics-based constraints to estimate the best ultrasound acquisition trajectories with respect to the available acoustic windows. We evaluate the developed method using virtual planning scenarios based on real patient data as well as for real robotic ultrasound acquisitions on a tissue-mimicking phantom. The proposed method yields superior image quality in comparison with a naive planning approach, while maintaining the necessary coverage of the target. We demonstrate that by taking image formation properties into account acquisition planning methods can outperform naive plannings. Furthermore, we show the need for such planning techniques, since naive approaches are not sufficient as they do not take the expected image quality into account.

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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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 36 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 7 19%
Student > Ph. D. Student 4 11%
Student > Bachelor 3 8%
Researcher 2 6%
Student > Postgraduate 2 6%
Other 6 17%
Unknown 12 33%
Readers by discipline Count As %
Engineering 8 22%
Computer Science 6 17%
Medicine and Dentistry 4 11%
Physics and Astronomy 1 3%
Neuroscience 1 3%
Other 1 3%
Unknown 15 42%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 November 2023.
All research outputs
#6,892,617
of 24,074,720 outputs
Outputs from International Journal of Computer Assisted Radiology and Surgery
#186
of 913 outputs
Outputs of similar age
#106,844
of 311,654 outputs
Outputs of similar age from International Journal of Computer Assisted Radiology and Surgery
#5
of 20 outputs
Altmetric has tracked 24,074,720 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 913 research outputs from this source. They receive a mean Attention Score of 3.1. This one has done well, scoring higher than 77% 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 311,654 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 64% of its contemporaries.
We're also able to compare this research output to 20 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.