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Minimally invasive registration for computer-assisted orthopedic surgery: combining tracked ultrasound and bone surface points via the P-IMLOP algorithm

Overview of attention for article published in International Journal of Computer Assisted Radiology and Surgery, April 2015
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (55th percentile)

Mentioned by

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1 Wikipedia page

Citations

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6 Dimensions

Readers on

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37 Mendeley
Title
Minimally invasive registration for computer-assisted orthopedic surgery: combining tracked ultrasound and bone surface points via the P-IMLOP algorithm
Published in
International Journal of Computer Assisted Radiology and Surgery, April 2015
DOI 10.1007/s11548-015-1188-z
Pubmed ID
Authors

Seth Billings, Hyun Jae Kang, Alexis Cheng, Emad Boctor, Peter Kazanzides, Russell Taylor

Abstract

We present a registration method for computer-assisted total hip replacement (THR) surgery, which we demonstrate to improve the state of the art by both reducing the invasiveness of current methods and increasing registration accuracy. A critical element of computer-guided procedures is the determination of the spatial correspondence between the patient and a computational model of patient anatomy. The current method for establishing this correspondence in robot-assisted THR is to register points intraoperatively sampled by a tracked pointer from the exposed proximal femur and, via auxiliary incisions, from the distal femur. In this paper, we demonstrate a noninvasive technique for sampling points on the distal femur using tracked B-mode ultrasound imaging and present a new algorithm for registering these data called Projected Iterative Most-Likely Oriented Point (P-IMLOP). Points and normal orientations of the distal bone surface are segmented from ultrasound images and registered to the patient model along with points sampled from the exposed proximal femur via a tracked pointer. The proposed approach is evaluated using a bone- and tissue-mimicking leg phantom constructed to enable accurate assessment of experimental registration accuracy with respect to a CT-image-based model of the phantom. These experiments demonstrate that localization of the femur shaft is greatly improved by tracked ultrasound. The experiments further demonstrate that, for ultrasound-based data, the P-IMLOP algorithm significantly improves registration accuracy compared to the standard ICP algorithm. Registration via tracked ultrasound and the P-IMLOP algorithm has high potential to reduce the invasiveness and improve the registration accuracy of computer-assisted orthopedic procedures.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 1 3%
Unknown 36 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 11%
Student > Master 4 11%
Student > Bachelor 3 8%
Student > Doctoral Student 3 8%
Researcher 3 8%
Other 8 22%
Unknown 12 32%
Readers by discipline Count As %
Engineering 8 22%
Medicine and Dentistry 8 22%
Computer Science 7 19%
Materials Science 1 3%
Unknown 13 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 13 August 2017.
All research outputs
#7,537,497
of 22,997,544 outputs
Outputs from International Journal of Computer Assisted Radiology and Surgery
#225
of 856 outputs
Outputs of similar age
#91,338
of 265,603 outputs
Outputs of similar age from International Journal of Computer Assisted Radiology and Surgery
#6
of 29 outputs
Altmetric has tracked 22,997,544 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 856 research outputs from this source. They receive a mean Attention Score of 3.1. This one has gotten more attention than average, scoring higher than 53% 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 265,603 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 55% of its contemporaries.
We're also able to compare this research output to 29 others from the same source and published within six weeks on either side of this one. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.