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Biomedical Image Registration

Overview of attention for book
Cover of 'Biomedical Image Registration'

Table of Contents

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    Book Overview
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    Chapter 1 Nonlinear Alignment of Whole Tractograms with the Linear Assignment Problem
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    Chapter 2 Learning-Based Affine Registration of Histological Images
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    Chapter 3 Enabling Manual Intervention for Otherwise Automated Registration of Large Image Series
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    Chapter 4 Towards Segmentation and Spatial Alignment of the Human Embryonic Brain Using Deep Learning for Atlas-Based Registration
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    Chapter 5 Learning Deformable Image Registration with Structure Guidance Constraints for Adaptive Radiotherapy
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    Chapter 6 Multilevel 2D-3D Intensity-Based Image Registration
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    Chapter 7 Towards Automated Spine Mobility Quantification: A Locally Rigid CT to X-ray Registration Framework
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    Chapter 8 Reinforced Redetection of Landmark in Pre- and Post-operative Brain Scan Using Anatomical Guidance for Image Alignment
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    Chapter 9 Deep Volumetric Feature Encoding for Biomedical Images
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    Chapter 10 Multi-channel Image Registration of Cardiac MR Using Supervised Feature Learning with Convolutional Encoder-Decoder Network
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    Chapter 11 Multi-channel Registration for Diffusion MRI: Longitudinal Analysis for the Neonatal Brain
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    Chapter 12 An Image Registration-Based Method for EPI Distortion Correction Based on Opposite Phase Encoding (COPE)
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    Chapter 13 Diffusion Tensor Driven Image Registration: A Deep Learning Approach
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    Chapter 14 Multimodal MRI Template Creation in the Ring-Tailed Lemur and Rhesus Macaque
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    Chapter 15 An Unsupervised Learning Approach to Discontinuity-Preserving Image Registration
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    Chapter 16 An Image Registration Framework for Discontinuous Mappings Along Cracks
Overall attention for this book and its chapters
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • Average Attention Score compared to outputs of the same age and source

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Citations

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Title
Biomedical Image Registration
Published by
Lecture notes in computer science, January 2020
DOI 10.1007/978-3-030-50120-4
ISBNs
978-3-03-050119-8, 978-3-03-050120-4
Editors

Špiclin, Žiga, McClelland, Jamie, Kybic, Jan, Goksel, Orcun

View on publisher site
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The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
 Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 June 2020.
All research outputs
#5,957,595
of 23,724,077 outputs
Outputs from Lecture notes in computer science
#1,859
of 8,159 outputs
Outputs of similar age
#124,019
of 460,439 outputs
Outputs of similar age from Lecture notes in computer science
#14
of 25 outputs
Altmetric has tracked 23,724,077 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 8,159 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has done well, scoring higher than 77% 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 460,439 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 72% of its contemporaries.
We're also able to compare this research output to 25 others from the same source and published within six weeks on either side of this one. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.

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