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Domain-adversarial neural networks to address the appearance variability of histopathology images

Overview of attention for book
Cover of 'Domain-adversarial neural networks to address the appearance variability of histopathology images'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Simultaneous Multiple Surface Segmentation Using Deep Learning
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    Chapter 2 A Deep Residual Inception Network for HEp-2 Cell Classification
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    Chapter 3 Joint Segmentation of Multiple Thoracic Organs in CT Images with Two Collaborative Deep Architectures
  5. Altmetric Badge
    Chapter 4 Accelerated Magnetic Resonance Imaging by Adversarial Neural Network
  6. Altmetric Badge
    Chapter 5 Left Atrium Segmentation in CT Volumes with Fully Convolutional Networks
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    Chapter 6 3D Randomized Connection Network with Graph-Based Inference
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    Chapter 7 Adversarial Training and Dilated Convolutions for Brain MRI Segmentation
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    Chapter 8 CNNs Enable Accurate and Fast Segmentation of Drusen in Optical Coherence Tomography
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    Chapter 9 Region-Aware Deep Localization Framework for Cervical Vertebrae in X-Ray Images
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    Chapter 10 Domain-Adversarial Neural Networks to Address the Appearance Variability of Histopathology Images
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    Chapter 11 Accurate Lung Segmentation via Network-Wise Training of Convolutional Networks
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    Chapter 12 Deep Residual Recurrent Neural Networks for Characterisation of Cardiac Cycle Phase from Echocardiograms
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    Chapter 13 Computationally Efficient Cardiac Views Projection Using 3D Convolutional Neural Networks
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    Chapter 14 Non-rigid Craniofacial 2D-3D Registration Using CNN-Based Regression
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    Chapter 15 A Deep Level Set Method for Image Segmentation
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    Chapter 16 Context-Based Normalization of Histological Stains Using Deep Convolutional Features
  18. Altmetric Badge
    Chapter 17 Transitioning Between Convolutional and Fully Connected Layers in Neural Networks
  19. Altmetric Badge
    Chapter 18 Quantifying the Impact of Type 2 Diabetes on Brain Perfusion Using Deep Neural Networks
  20. Altmetric Badge
    Chapter 19 Multi-stage Diagnosis of Alzheimer’s Disease with Incomplete Multimodal Data via Multi-task Deep Learning
  21. Altmetric Badge
    Chapter 20 A Multi-scale CNN and Curriculum Learning Strategy for Mammogram Classification
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    Chapter 21 Analyzing Microscopic Images of Peripheral Blood Smear Using Deep Learning
  23. Altmetric Badge
    Chapter 22 AGNet: Attention-Guided Network for Surgical Tool Presence Detection
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    Chapter 23 Pathological Pulmonary Lobe Segmentation from CT Images Using Progressive Holistically Nested Neural Networks and Random Walker
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    Chapter 24 End-to-End Unsupervised Deformable Image Registration with a Convolutional Neural Network
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    Chapter 25 Stain Colour Normalisation to Improve Mitosis Detection on Breast Histology Images
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    Chapter 26 3D FCN Feature Driven Regression Forest-Based Pancreas Localization and Segmentation
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    Chapter 27 A Unified Framework for Tumor Proliferation Score Prediction in Breast Histopathology
  29. Altmetric Badge
    Chapter 28 Generalised Dice Overlap as a Deep Learning Loss Function for Highly Unbalanced Segmentations
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    Chapter 29 ssEMnet: Serial-Section Electron Microscopy Image Registration Using a Spatial Transformer Network with Learned Features
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    Chapter 30 Fully Convolutional Regression Network for Accurate Detection of Measurement Points
  32. Altmetric Badge
    Chapter 31 Fast Predictive Simple Geodesic Regression
  33. Altmetric Badge
    Chapter 32 Learning Spatio-Temporal Aggregation for Fetal Heart Analysis in Ultrasound Video
  34. Altmetric Badge
    Chapter 33 Fast, Simple Calcium Imaging Segmentation with Fully Convolutional Networks
  35. Altmetric Badge
    Chapter 34 Self-supervised Learning for Spinal MRIs
  36. Altmetric Badge
    Chapter 35 Skin Lesion Segmentation via Deep RefineNet
  37. Altmetric Badge
    Chapter 36 Multi-scale Networks for Segmentation of Brain Magnetic Resonance Images
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    Chapter 37 Deep Learning for Automatic Detection of Abnormal Findings in Breast Mammography
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    Chapter 38 Grey Matter Segmentation in Spinal Cord MRIs via 3D Convolutional Encoder Networks with Shortcut Connections
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    Chapter 39 Mapping Multi-Modal Routine Imaging Data to a Single Reference via Multiple Templates
  41. Altmetric Badge
    Chapter 40 Automated Detection of Epileptogenic Cortical Malformations Using Multimodal MRI
  42. Altmetric Badge
    Chapter 41 Prediction of Amyloidosis from Neuropsychological and MRI Data for Cost Effective Inclusion of Pre-symptomatic Subjects in Clinical Trials
  43. Altmetric Badge
    Chapter 42 Automated Multimodal Breast CAD Based on Registration of MRI and Two View Mammography
  44. Altmetric Badge
    Chapter 43 EMR-Radiological Phenotypes in Diseases of the Optic Nerve and Their Association with Visual Function
  45. Altmetric Badge
    Chapter 44 Erratum to: Fast Predictive Simple Geodesic Regression
Attention for Chapter 29: ssEMnet: Serial-Section Electron Microscopy Image Registration Using a Spatial Transformer Network with Learned Features
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About this Attention Score

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  • Average Attention Score compared to outputs of the same age and source

Mentioned by

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Citations

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45 Mendeley
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Chapter title
ssEMnet: Serial-Section Electron Microscopy Image Registration Using a Spatial Transformer Network with Learned Features
Chapter number 29
Book title
Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support
Published in
arXiv, September 2017
DOI 10.1007/978-3-319-67558-9_29
Book ISBNs
978-3-31-967557-2, 978-3-31-967558-9
Authors

Inwan Yoo, David G. C. Hildebrand, Willie F. Tobin, Wei-Chung Allen Lee, Won-Ki Jeong, Yoo, Inwan, Hildebrand, David G. C., Tobin, Willie F., Lee, Wei-Chung Allen, Jeong, Won-Ki

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X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 45 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 22%
Student > Master 8 18%
Researcher 5 11%
Other 2 4%
Student > Doctoral Student 1 2%
Other 2 4%
Unknown 17 38%
Readers by discipline Count As %
Computer Science 14 31%
Engineering 6 13%
Agricultural and Biological Sciences 3 7%
Physics and Astronomy 2 4%
Biochemistry, Genetics and Molecular Biology 1 2%
Other 2 4%
Unknown 17 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 26 July 2017.
All research outputs
#15,751,441
of 24,002,307 outputs
Outputs from arXiv
#351,916
of 1,011,770 outputs
Outputs of similar age
#191,810
of 319,219 outputs
Outputs of similar age from arXiv
#8,714
of 20,609 outputs
Altmetric has tracked 24,002,307 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
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 gotten more attention than average, scoring higher than 60% 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 319,219 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 20,609 others from the same source and published within six weeks on either side of this one. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.

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