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Machine Learning in Medical Imaging

Overview of attention for book
Cover of 'Machine Learning in Medical Imaging'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Fast Automatic Detection of Calcified Coronary Lesions in 3D Cardiac CT Images
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    Chapter 2 Automated Intervertebral Disc Detection from Low Resolution, Sparse MRI Images for the Planning of Scan Geometries
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    Chapter 3 Content-Based Medical Image Retrieval with Metric Learning via Rank Correlation
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    Chapter 4 A Hyper-parameter Inference for Radon Transformed Image Reconstruction Using Bayesian Inference
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    Chapter 5 Patch-Based Generative Shape Model and MDL Model Selection for Statistical Analysis of Archipelagos
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    Chapter 6 Prediction of Dementia by Hippocampal Shape Analysis
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    Chapter 7 Multi-Class Sparse Bayesian Regression for Neuroimaging Data Analysis
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    Chapter 8 Appearance Normalization of Histology Slides
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    Chapter 9 Parallel Mean Shift for Interactive Volume Segmentation
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    Chapter 10 Soft Tissue Discrimination Using Magnetic Resonance Elastography with a New Elastic Level Set Model
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    Chapter 11 Fast and Automatic Heart Isolation in 3D CT Volumes: Optimal Shape Initialization
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    Chapter 12 Relation-Aware Spreadsheets for Multimodal Volume Segmentation and Visualization
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    Chapter 13 A Bayesian Learning Application to Automated Tumour Segmentation for Tissue Microarray Analysis
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    Chapter 14 Generalized Sparse Classifiers for Decoding Cognitive States in fMRI
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    Chapter 15 Manifold Learning for Biomarker Discovery in MR Imaging
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    Chapter 16 Machine Learning in Medical Imaging
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    Chapter 17 Fully Automatic Joint Segmentation for Computer-Aided Diagnosis and Planning
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    Chapter 18 Machine Learning in Medical Imaging
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    Chapter 19 Feature Extraction for fMRI-Based Human Brain Activity Recognition
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    Chapter 20 Sparse Spatio-temporal Inference of Electromagnetic Brain Sources
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    Chapter 21 Optimal Gaussian Mixture Models of Tissue Intensities in Brain MRI of Patients with Multiple-Sclerosis
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    Chapter 22 Preliminary Study on Appearance-Based Detection of Anatomical Point Landmarks in Body Trunk CT Images
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    Chapter 23 Principal-Component Massive-Training Machine-Learning Regression for False-Positive Reduction in Computer-Aided Detection of Polyps in CT Colonography
Overall attention for this book and its chapters
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Mentioned by

patent
1 patent

Citations

dimensions_citation
17 Dimensions

Readers on

mendeley
7 Mendeley
Summary Patents Dimensions citations
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Title
Machine Learning in Medical Imaging
Published by
ADS, January 2010
DOI 10.1007/978-3-642-15948-0
ISBNs
978-3-64-215947-3, 978-3-64-215948-0
Editors

Wang, Fei, Yan, Pingkun, Suzuki, Kenji, Shen, Dinggang

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 29%
Lecturer > Senior Lecturer 1 14%
Student > Bachelor 1 14%
Lecturer 1 14%
Student > Ph. D. Student 1 14%
Other 1 14%
Readers by discipline Count As %
Computer Science 6 86%
Unspecified 1 14%
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 16 August 2022.
All research outputs
#7,576,061
of 23,103,436 outputs
Outputs from ADS
#9,338
of 37,502 outputs
Outputs of similar age
#48,915
of 165,238 outputs
Outputs of similar age from ADS
#275
of 799 outputs
Altmetric has tracked 23,103,436 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 37,502 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 29th percentile – i.e., 29% of its peers scored the same or lower than it.
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 165,238 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 799 others from the same source and published within six weeks on either side of this one. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.

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