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Liver segmentation: indications, techniques and future directions

Overview of attention for article published in Insights into Imaging, June 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

Mentioned by

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3 X users
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7 patents
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2 Facebook pages

Citations

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149 Dimensions

Readers on

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233 Mendeley
Title
Liver segmentation: indications, techniques and future directions
Published in
Insights into Imaging, June 2017
DOI 10.1007/s13244-017-0558-1
Pubmed ID
Authors

Akshat Gotra, Lojan Sivakumaran, Gabriel Chartrand, Kim-Nhien Vu, Franck Vandenbroucke-Menu, Claude Kauffmann, Samuel Kadoury, Benoît Gallix, Jacques A. de Guise, An Tang

Abstract

Liver volumetry has emerged as an important tool in clinical practice. Liver volume is assessed primarily via organ segmentation of computed tomography (CT) and magnetic resonance imaging (MRI) images. The goal of this paper is to provide an accessible overview of liver segmentation targeted at radiologists and other healthcare professionals. Using images from CT and MRI, this paper reviews the indications for liver segmentation, technical approaches used in segmentation software and the developing roles of liver segmentation in clinical practice. Liver segmentation for volumetric assessment is indicated prior to major hepatectomy, portal vein embolisation, associating liver partition and portal vein ligation for staged hepatectomy (ALPPS) and transplant. Segmentation software can be categorised according to amount of user input involved: manual, semi-automated and fully automated. Manual segmentation is considered the "gold standard" in clinical practice and research, but is tedious and time-consuming. Increasingly automated segmentation approaches are more robust, but may suffer from certain segmentation pitfalls. Emerging applications of segmentation include surgical planning and integration with MRI-based biomarkers. Liver segmentation has multiple clinical applications and is expanding in scope. Clinicians can employ semi-automated or fully automated segmentation options to more efficiently integrate volumetry into clinical practice. • Liver volume is assessed via organ segmentation on CT and MRI examinations. • Liver segmentation is used for volume assessment prior to major hepatic procedures. • Segmentation approaches may be categorised according to the amount of user input involved. • Emerging applications include surgical planning and integration with MRI-based biomarkers.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users 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 233 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 233 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 32 14%
Student > Ph. D. Student 30 13%
Student > Master 26 11%
Other 19 8%
Student > Bachelor 19 8%
Other 43 18%
Unknown 64 27%
Readers by discipline Count As %
Medicine and Dentistry 54 23%
Computer Science 40 17%
Engineering 32 14%
Physics and Astronomy 8 3%
Biochemistry, Genetics and Molecular Biology 4 2%
Other 20 9%
Unknown 75 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 14. 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 03 October 2023.
All research outputs
#2,455,891
of 25,220,525 outputs
Outputs from Insights into Imaging
#129
of 1,191 outputs
Outputs of similar age
#44,769
of 323,503 outputs
Outputs of similar age from Insights into Imaging
#2
of 8 outputs
Altmetric has tracked 25,220,525 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,191 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.1. This one has done well, scoring higher than 89% 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 323,503 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than 6 of them.