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Computational Methods and Clinical Applications for Spine Imaging

Overview of attention for book
Cover of 'Computational Methods and Clinical Applications for Spine Imaging'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Automated Pedicle Screw Size and Trajectory Planning by Maximization of Fastening Strength
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    Chapter 2 Automatic Modic Changes Classification in Spinal MRI
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    Chapter 3 Patient Registration via Topologically Encoded Depth Projection Images in Spine Surgery
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    Chapter 4 Automatic Localisation of Vertebrae in DXA Images Using Random Forest Regression Voting
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    Chapter 5 Robust CT to US 3D-3D Registration by Using Principal Component Analysis and Kalman Filtering
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    Chapter 6 Cortical Bone Thickness Estimation in CT Images: A Model-Based Approach Without Profile Fitting
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    Chapter 7 Multi-atlas Segmentation with Joint Label Fusion of Osteoporotic Vertebral Compression Fractures on CT
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    Chapter 8 Statistical Shape Model Construction of Lumbar Vertebrae and Intervertebral Discs in Segmentation for Discectomy Surgery Simulation
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    Chapter 9 Automatic Intervertebral Discs Localization and Segmentation: A Vertebral Approach
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    Chapter 10 Segmentation of Intervertebral Discs in 3D MRI Data Using Multi-atlas Based Registration
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    Chapter 11 Deformable Model-Based Segmentation of Intervertebral Discs from MR Spine Images by Using the SSC Descriptor
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    Chapter 12 3D Intervertebral Disc Segmentation from MRI Using Supervoxel-Based CRFs
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    Chapter 13 Automatic Intervertebral Disc Localization and Segmentation in 3D MR Images Based on Regression Forests and Active Contours
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    Chapter 14 Localization and Segmentation of 3D Intervertebral Discs from MR Images via a Learning Based Method: A Validation Framework
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    Chapter 15 Automated Intervertebral Disc Segmentation Using Probabilistic Shape Estimation and Active Shape Models
Overall attention for this book and its chapters
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About this Attention Score

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

Mentioned by

patent
2 patents

Citations

dimensions_citation
5 Dimensions

Readers on

mendeley
59 Mendeley
Summary Patents Dimensions citations
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Computational Methods and Clinical Applications for Spine Imaging
Published by
Lecture notes in computer science, January 2016
DOI 10.1007/978-3-319-41827-8
ISBNs
978-3-31-941826-1, 978-3-31-941827-8
Editors

Vrtovec, Tomaž, Yao, Jianhua, Glocker, Ben, Klinder, Tobias, Frangi, Alejandro, Zheng, Guoyan, Li, Shuo

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 2%
Unknown 58 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 22 37%
Student > Master 7 12%
Student > Bachelor 6 10%
Other 5 8%
Researcher 5 8%
Other 8 14%
Unknown 6 10%
Readers by discipline Count As %
Engineering 21 36%
Computer Science 12 20%
Medicine and Dentistry 6 10%
Physics and Astronomy 2 3%
Agricultural and Biological Sciences 2 3%
Other 6 10%
Unknown 10 17%
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 25 July 2023.
All research outputs
#7,522,616
of 22,958,253 outputs
Outputs from Lecture notes in computer science
#2,489
of 8,134 outputs
Outputs of similar age
#123,636
of 394,315 outputs
Outputs of similar age from Lecture notes in computer science
#260
of 582 outputs
Altmetric has tracked 22,958,253 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 8,134 research outputs from this source. They receive a mean Attention Score of 5.0. This one has gotten more attention than average, scoring higher than 54% 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 394,315 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 582 others from the same source and published within six weeks on either side of this one. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.

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