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Deformable multimodal registration for navigation in beating-heart cardiac surgery

Overview of attention for article published in International Journal of Computer Assisted Radiology and Surgery, March 2019
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#28 of 386)
  • Good Attention Score compared to outputs of the same age (71st percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

Mentioned by

twitter
8 tweeters

Readers on

mendeley
5 Mendeley
Title
Deformable multimodal registration for navigation in beating-heart cardiac surgery
Published in
International Journal of Computer Assisted Radiology and Surgery, March 2019
DOI 10.1007/s11548-019-01932-2
Pubmed ID
Authors

Jacob J. Peoples, Gianluigi Bisleri, Randy E. Ellis

Abstract

Minimally invasive beating-heart surgery is currently performed using endoscopes and without navigation. Registration of intraoperative ultrasound to a preoperative cardiac CT scan is a valuable step toward image-guided navigation. The registration was achieved by first extracting a representative point set from each ultrasound image in the sequence using a deformable registration. A template shape representing the cardiac chambers was deformed through a hierarchy of affine transformations to match each ultrasound image using a generalized expectation maximization algorithm. These extracted point sets were matched to the CT by exhaustively searching over a large number of precomputed slices of 3D geometry. The result is a similarity transformation mapping the intraoperative ultrasound to preoperative CT. Complete data sets were acquired for four patients. Transesophageal echocardiography ultrasound sequences were deformably registered to a model of oriented points with a mean error of 2.3 mm. Ultrasound and CT scans were registered to a mean of 3 mm, which is comparable to the error of 2.8 mm expected by merging ultrasound registration with uncertainty of cardiac CT. The proposed algorithm registered 3D CT with dynamic 2D intraoperative imaging. The algorithm aligned the images in both space and time, needing neither dynamic CT imaging nor intraoperative electrocardiograms. The accuracy was sufficient for navigation in thoracoscopically guided beating-heart surgery.

Twitter Demographics

The data shown below were collected from the profiles of 8 tweeters 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 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 40%
Student > Ph. D. Student 1 20%
Researcher 1 20%
Unspecified 1 20%
Readers by discipline Count As %
Engineering 2 40%
Economics, Econometrics and Finance 1 20%
Medicine and Dentistry 1 20%
Unspecified 1 20%

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 29 March 2019.
All research outputs
#2,421,248
of 13,560,201 outputs
Outputs from International Journal of Computer Assisted Radiology and Surgery
#28
of 386 outputs
Outputs of similar age
#71,336
of 255,459 outputs
Outputs of similar age from International Journal of Computer Assisted Radiology and Surgery
#3
of 19 outputs
Altmetric has tracked 13,560,201 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 386 research outputs from this source. They receive a mean Attention Score of 2.7. This one has done particularly well, scoring higher than 92% 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 255,459 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 71% of its contemporaries.
We're also able to compare this research output to 19 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.