↓ Skip to main content
What is this page? Embed badge

Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS Challenges

Overview of attention for book
Cover of 'Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS Challenges'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Multiview Machine Learning Using an Atlas of Cardiac Cycle Motion
  3. Altmetric Badge
    Chapter 2 Joint Myocardial Registration and Segmentation of Cardiac BOLD MRI
  4. Altmetric Badge
    Chapter 3 Transfer Learning for the Fully Automatic Segmentation of Left Ventricle Myocardium in Porcine Cardiac Cine MR Images
  5. Altmetric Badge
    Chapter 4 Left Atrial Appendage Neck Modeling for Closure Surgery
  6. Altmetric Badge
    Chapter 5 Detection of Substances in the Left Atrial Appendage by Spatiotemporal Motion Analysis Based on 4D-CT
  7. Altmetric Badge
    Chapter 6 Estimation of Healthy and Fibrotic Tissue Distributions in DE-CMR Incorporating CINE-CMR in an EM Algorithm
  8. Altmetric Badge
    Chapter 7 Multilevel Non-parametric Groupwise Registration in Cardiac MRI: Application to Explanted Porcine Hearts
  9. Altmetric Badge
    Chapter 8 GridNet with Automatic Shape Prior Registration for Automatic MRI Cardiac Segmentation
  10. Altmetric Badge
    Chapter 9 A Radiomics Approach to Computer-Aided Diagnosis with Cardiac Cine-MRI
  11. Altmetric Badge
    Chapter 10 Fast Fully-Automatic Cardiac Segmentation in MRI Using MRF Model Optimization, Substructures Tracking and B-Spline Smoothing
  12. Altmetric Badge
    Chapter 11 Automatic Segmentation and Disease Classification Using Cardiac Cine MR Images
  13. Altmetric Badge
    Chapter 12 An Exploration of 2D and 3D Deep Learning Techniques for Cardiac MR Image Segmentation
  14. Altmetric Badge
    Chapter 13 Automatic Cardiac Disease Assessment on cine-MRI via Time-Series Segmentation and Domain Specific Features
  15. Altmetric Badge
    Chapter 14 2D-3D Fully Convolutional Neural Networks for Cardiac MR Segmentation
  16. Altmetric Badge
    Chapter 15 Densely Connected Fully Convolutional Network for Short-Axis Cardiac Cine MR Image Segmentation and Heart Diagnosis Using Random Forest
  17. Altmetric Badge
    Chapter 16 Class-Balanced Deep Neural Network for Automatic Ventricular Structure Segmentation
  18. Altmetric Badge
    Chapter 17 Automatic Segmentation of LV and RV in Cardiac MRI
  19. Altmetric Badge
    Chapter 18 Automatic Multi-Atlas Segmentation of Myocardium with SVF-Net
  20. Altmetric Badge
    Chapter 19 3D Convolutional Networks for Fully Automatic Fine-Grained Whole Heart Partition
  21. Altmetric Badge
    Chapter 20 Multi-label Whole Heart Segmentation Using CNNs and Anatomical Label Configurations
  22. Altmetric Badge
    Chapter 21 Multi-Planar Deep Segmentation Networks for Cardiac Substructures from MRI and CT
  23. Altmetric Badge
    Chapter 22 Local Probabilistic Atlases and a Posteriori Correction for the Segmentation of Heart Images
  24. Altmetric Badge
    Chapter 23 Hybrid Loss Guided Convolutional Networks for Whole Heart Parsing
  25. Altmetric Badge
    Chapter 24 3D Deeply-Supervised U-Net Based Whole Heart Segmentation
  26. Altmetric Badge
    Chapter 25 MRI Whole Heart Segmentation Using Discrete Nonlinear Registration and Fast Non-local Fusion
  27. Altmetric Badge
    Chapter 26 Automatic Whole Heart Segmentation Using Deep Learning and Shape Context
  28. Altmetric Badge
    Chapter 27 Automatic Whole Heart Segmentation in CT Images Based on Multi-atlas Image Registration
Attention for Chapter 9: A Radiomics Approach to Computer-Aided Diagnosis with Cardiac Cine-MRI
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

Mentioned by

twitter
9 tweeters

Citations

dimensions_citation
28 Dimensions

Readers on

mendeley
50 Mendeley
Summary Twitter 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.
Chapter title
A Radiomics Approach to Computer-Aided Diagnosis with Cardiac Cine-MRI
Chapter number 9
Book title
Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS Challenges
Published in
arXiv, September 2017
DOI 10.1007/978-3-319-75541-0_9
Book ISBNs
978-3-31-975540-3, 978-3-31-975541-0
Authors

Irem Cetin, Gerard Sanroma, Steffen E. Petersen, Sandy Napel, Oscar Camara, Miguel-Angel Gonzalez Ballester, Karim Lekadir

View on publisher site
Twitter Demographics

Twitter Demographics

The data shown below were collected from the profiles of 9 tweeters 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 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 50 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 16%
Student > Master 6 12%
Researcher 5 10%
Student > Bachelor 4 8%
Other 4 8%
Other 10 20%
Unknown 13 26%
Readers by discipline Count As %
Computer Science 17 34%
Engineering 6 12%
Medicine and Dentistry 4 8%
Agricultural and Biological Sciences 1 2%
Chemical Engineering 1 2%
Other 2 4%
Unknown 19 38%
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 October 2019.
All research outputs
#13,802,202
of 24,099,692 outputs
Outputs from arXiv
#206,161
of 1,020,419 outputs
Outputs of similar age
#153,878
of 319,505 outputs
Outputs of similar age from arXiv
#4,123
of 20,380 outputs
Altmetric has tracked 24,099,692 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,020,419 research outputs from this source. They receive a mean Attention Score of 4.0. This one has done well, scoring higher than 78% 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 319,505 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 50% of its contemporaries.
We're also able to compare this research output to 20,380 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.

This page is provided by Altmetric.