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Medical Computer Vision. Recognition Techniques and Applications in Medical Imaging

Overview of attention for book
Cover of 'Medical Computer Vision. Recognition Techniques and Applications in Medical Imaging'

Table of Contents

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    Book Overview
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    Chapter 1 Real-Time 2D/3D Deformable Registration Using Metric Learning
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    Chapter 2 Groupwise Spectral Log-Demons Framework for Atlas Construction
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    Chapter 3 Robust Anatomical Correspondence Detection by Graph Matching with Sparsity Constraint
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    Chapter 4 Semi-supervised Segmentation Using Multiple Segmentation Hypotheses from a Single Atlas
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    Chapter 5 Carotid Artery Wall Segmentation by Coupled Surface Graph Cuts
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    Chapter 6 Graph Cut Segmentation Using a Constrained Statistical Model with Non-linear and Sparse Shape Optimization
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    Chapter 7 Novel Context Rich LoCo and GloCo Features with Local and Global Shape Constraints for Segmentation of 3D Echocardiograms with Random Forests
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    Chapter 8 Novel Vector-Valued Approach to Automatic Brain Tissue Classification
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    Chapter 9 Atlas-Based Whole-Body PET-CT Segmentation Using a Passive Contour Distance
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    Chapter 10 Spatially Aware Patch-Based Segmentation (SAPS): An Alternative Patch-Based Segmentation Framework
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    Chapter 11 Efficient Geometrical Potential Force Computation for Deformable Model Segmentation
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    Chapter 12 Shape Prior Model for Media-Adventitia Border Segmentation in IVUS Using Graph Cut
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    Chapter 13 Multiple Atlases-Based Joint Labeling of Human Cortical Sulcal Curves
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    Chapter 14 Medical Computer Vision. Recognition Techniques and Applications in Medical Imaging
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    Chapter 15 Oblique Random Forests for 3-D Vessel Detection Using Steerable Filters and Orthogonal Subspace Filtering
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    Chapter 16 Pipeline for Tracking Neural Progenitor Cells
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    Chapter 17 Automatic Heart Isolation in 3D CT Images
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    Chapter 18 Randomness and Sparsity Induced Codebook Learning with Application to Cancer Image Classification
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    Chapter 19 Context Enhanced Graphical Model for Object Localization in Medical Images
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    Chapter 20 A Cascade Learning Method for Liver Lesion Detection in CT Images
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    Chapter 21 Medical Computer Vision. Recognition Techniques and Applications in Medical Imaging
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    Chapter 22 Automatic Extraction of the Curved Midsagittal Brain Surface on MR Images
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    Chapter 23 Identification of Malignant Breast Tumors Based on Acoustic Attenuation Mapping of Conventional Ultrasound Images
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    Chapter 24 What Genes Tell about Iris Appearance
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    Chapter 25 Robust Dense Endoscopic Stereo Reconstruction for Minimally Invasive Surgery
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    Chapter 26 Model-Based Human Teeth Shape Recovery from a Single Optical Image with Unknown Illumination
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    Chapter 27 Brain Tumor Cell Density Estimation from Multi-modal MR Images Based on a Synthetic Tumor Growth Model
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    Chapter 28 Current-Based 4D Shape Analysis for the Mechanical Personalization of Heart Models
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 (65th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (61st percentile)

Mentioned by

wikipedia
1 Wikipedia page

Citations

dimensions_citation
4 Dimensions

Readers on

mendeley
5 Mendeley
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Title
Medical Computer Vision. Recognition Techniques and Applications in Medical Imaging
Published by
Lecture notes in computer science, January 2013
DOI 10.1007/978-3-642-36620-8
ISBNs
978-3-64-236619-2, 978-3-64-236620-8
Authors

Bjoern H. Menze, Georg Langs, Le Lu, Albert Montillo, Zhuowen Tu, Antonio Criminisi

Editors

Menze, Bjoern H., Langs, Georg, Lu, Le, Montillo, Albert, Tu, Zhuowen, Criminisi, Antonio

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 80%
Lecturer 1 20%
Student > Master 1 20%
Readers by discipline Count As %
Computer Science 2 40%
Physics and Astronomy 1 20%
Business, Management and Accounting 1 20%
Medicine and Dentistry 1 20%
Engineering 1 20%
Other 0 0%

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 05 November 2014.
All research outputs
#2,619,994
of 9,723,598 outputs
Outputs from Lecture notes in computer science
#1,977
of 7,142 outputs
Outputs of similar age
#87,041
of 269,635 outputs
Outputs of similar age from Lecture notes in computer science
#32
of 104 outputs
Altmetric has tracked 9,723,598 research outputs across all sources so far. This one has received more attention than most of these and is in the 57th percentile.
So far Altmetric has tracked 7,142 research outputs from this source. They receive a mean Attention Score of 4.3. This one has gotten more attention than average, scoring higher than 59% 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 269,635 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 65% of its contemporaries.
We're also able to compare this research output to 104 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.