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Capsule Networks against Medical Imaging Data Challenges

Overview of attention for book
Cover of 'Capsule Networks against Medical Imaging Data Challenges'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Blood-Flow Estimation in the Hepatic Arteries Based on 3D/2D Angiography Registration
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    Chapter 2 Automated Quantification of Blood Flow Velocity from Time-Resolved CT Angiography
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    Chapter 3 Multiple Device Segmentation for Fluoroscopic Imaging Using Multi-task Learning
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    Chapter 4 Segmentation of the Aorta Using Active Contours with Histogram-Based Descriptors
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    Chapter 5 Layer Separation in X-ray Angiograms for Vessel Enhancement with Fully Convolutional Network
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    Chapter 6 Generation of a HER2 Breast Cancer Gold-Standard Using Supervised Learning from Multiple Experts
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    Chapter 7 Deep Learning-Based Detection and Segmentation for BVS Struts in IVOCT Images
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    Chapter 8 Towards Automatic Measurement of Type B Aortic Dissection Parameters: Methods, Applications and Perspective
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    Chapter 9 Prediction of FFR from IVUS Images Using Machine Learning
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    Chapter 10 Deep Learning Retinal Vessel Segmentation from a Single Annotated Example: An Application of Cyclic Generative Adversarial Neural Networks
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    Chapter 11 An Efficient and Comprehensive Labeling Tool for Large-Scale Annotation of Fundus Images
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    Chapter 12 Crowd Disagreement About Medical Images Is Informative
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    Chapter 13 Imperfect Segmentation Labels: How Much Do They Matter?
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    Chapter 14 Crowdsourcing Annotation of Surgical Instruments in Videos of Cataract Surgery
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    Chapter 15 Four-Dimensional ASL MR Angiography Phantoms with Noise Learned by Neural Styling
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    Chapter 16 Feature Learning Based on Visual Similarity Triplets in Medical Image Analysis: A Case Study of Emphysema in Chest CT Scans
  18. Altmetric Badge
    Chapter 17 Capsule Networks Against Medical Imaging Data Challenges
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    Chapter 18 Fully Automatic Segmentation of Coronary Arteries Based on Deep Neural Network in Intravascular Ultrasound Images
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    Chapter 19 Weakly-Supervised Learning for Tool Localization in Laparoscopic Videos
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    Chapter 20 Radiology Objects in COntext (ROCO): A Multimodal Image Dataset
  22. Altmetric Badge
    Chapter 21 Improving Out-of-Sample Prediction of Quality of MRIQC
Overall attention for this book and its chapters
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (76th percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

Mentioned by

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10 X users
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1 patent

Citations

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5 Dimensions

Readers on

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14 Mendeley
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Title
Capsule Networks against Medical Imaging Data Challenges
Published by
arXiv, July 2018
DOI 10.1007/978-3-030-01364-6
ISBNs
978-3-03-001363-9, 978-3-03-001364-6
Authors

Amelia Jiménez-Sánchez, Shadi Albarqouni, Diana Mateus

Editors

Stoyanov, Danail, Taylor, Zeike, Balocco, Simone, Sznitman, Raphael, Martel, Anne, Maier-Hein, Lena, Duong, Luc, Zahnd, Guillaume, Demirci, Stefanie, Albarqouni, Shadi, Lee, Su-Lin, Moriconi, Stefano, Cheplygina, Veronika, Mateus, Diana, Trucco, Emanuele, Granger, Eric, Jannin, Pierre

X Demographics

X Demographics

The data shown below were collected from the profiles of 10 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 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 22 157%
Student > Ph. D. Student 20 143%
Researcher 8 57%
Student > Bachelor 5 36%
Other 5 36%
Other 14 100%
Readers by discipline Count As %
Computer Science 41 293%
Engineering 10 71%
Medicine and Dentistry 3 21%
Chemistry 2 14%
Physics and Astronomy 2 14%
Other 9 64%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 20 September 2021.
All research outputs
#4,250,430
of 24,002,307 outputs
Outputs from arXiv
#85,410
of 1,011,770 outputs
Outputs of similar age
#78,201
of 332,560 outputs
Outputs of similar age from arXiv
#2,270
of 23,580 outputs
Altmetric has tracked 24,002,307 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 1,011,770 research outputs from this source. They receive a mean Attention Score of 4.0. This one has done particularly well, scoring higher than 91% 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 332,560 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 76% of its contemporaries.
We're also able to compare this research output to 23,580 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.