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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
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    Chapter 1 Function MRI Representation Learning via Self-supervised Transformer for Automated Brain Disorder Analysis
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    Chapter 2 Predicting Age-related Macular Degeneration Progression with Longitudinal Fundus Images Using Deep Learning
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    Chapter 3 Region-Guided Channel-Wise Attention Network for Accelerated MRI Reconstruction
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    Chapter 4 Student Becomes Decathlon Master in Retinal Vessel Segmentation via Dual-Teacher Multi-target Domain Adaptation
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    Chapter 5 Rethinking Degradation: Radiograph Super-Resolution via AID-SRGAN
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    Chapter 6 3D Segmentation with Fully Trainable Gabor Kernels and Pearson's Correlation Coefficient
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    Chapter 7 A More Design-Flexible Medical Transformer for Volumetric Image Segmentation
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    Chapter 8 Dcor-VLDet: A Vertebra Landmark Detection Network for Scoliosis Assessment with Dual Coordinate System
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    Chapter 9 Plug-and-Play Shape Refinement Framework for Multi-site and Lifespan Brain Skull Stripping
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    Chapter 10 A Coarse-to-Fine Network for Craniopharyngioma Segmentation
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    Chapter 11 Patch-Level Instance-Group Discrimination with Pretext-Invariant Learning for Colitis Scoring
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    Chapter 12 AutoMO-Mixer: An Automated Multi-objective Mixer Model for Balanced, Safe and Robust Prediction in Medicine
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    Chapter 13 Memory Transformers for Full Context and High-Resolution 3D Medical Segmentation
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    Chapter 14 Whole Mammography Diagnosis via Multi-instance Supervised Discriminative Localization and Classification
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    Chapter 15 Cross Task Temporal Consistency for Semi-supervised Medical Image Segmentation
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    Chapter 16 U-Net vs Transformer: Is U-Net Outdated in Medical Image Registration?
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    Chapter 17 UNet-eVAE: Iterative Refinement Using VAE Embodied Learning for Endoscopic Image Segmentation
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    Chapter 18 Dynamic Linear Transformer for 3D Biomedical Image Segmentation
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    Chapter 19 Automatic Grading of Emphysema by Combining 3D Lung Tissue Appearance and Deformation Map Using a Two-Stream Fully Convolutional Neural Network
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    Chapter 20 A Novel Two-Stage Multi-view Low-Rank Sparse Subspace Clustering Approach to Explore the Relationship Between Brain Function and Structure
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    Chapter 21 Fast Image-Level MRI Harmonization via Spectrum Analysis
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    Chapter 22 CT2CXR: CT-based CXR Synthesis for Covid-19 Pneumonia Classification
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    Chapter 23 Harmonization of Multi-site Cortical Data Across the Human Lifespan
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    Chapter 24 Head and Neck Vessel Segmentation with Connective Topology Using Affinity Graph
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    Chapter 25 Coarse Retinal Lesion Annotations Refinement via Prototypical Learning
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    Chapter 26 Nuclear Segmentation and Classification: On Color and Compression Generalization
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    Chapter 27 Understanding Clinical Progression of Late-Life Depression to Alzheimer’s Disease Over 5 Years with Structural MRI
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    Chapter 28 ClinicalRadioBERT: Knowledge-Infused Few Shot Learning for Clinical Notes Named Entity Recognition
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    Chapter 29 Graph Representation Neural Architecture Search for Optimal Spatial/Temporal Functional Brain Network Decomposition
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    Chapter 30 Driving Points Prediction for Abdominal Probabilistic Registration
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    Chapter 31 CircleSnake: Instance Segmentation with Circle Representation
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    Chapter 32 Vertebrae Localization, Segmentation and Identification Using a Graph Optimization and an Anatomic Consistency Cycle
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    Chapter 33 Coronary Ostia Localization Using Residual U-Net with Heatmap Matching and 3D DSNT
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    Chapter 34 AMLP-Conv, a 3D Axial Long-range Interaction Multilayer Perceptron for CNNs
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    Chapter 35 Neural State-Space Modeling with Latent Causal-Effect Disentanglement
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    Chapter 36 Adaptive Unified Contrastive Learning for Imbalanced Classification
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    Chapter 37 Prediction of HPV-Associated Genetic Diversity for Squamous Cell Carcinoma of Head and Neck Cancer Based on $$^{18}$$ 18 F-FDG PET/CT
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    Chapter 38 TransWS: Transformer-Based Weakly Supervised Histology Image Segmentation
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    Chapter 39 Contextual Attention Network: Transformer Meets U-Net
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    Chapter 40 Intelligent Masking: Deep Q-Learning for Context Encoding in Medical Image Analysis
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    Chapter 41 A New Lightweight Architecture and a Class Imbalance Aware Loss Function for Multi-label Classification of Intracranial Hemorrhages
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    Chapter 42 Spherical Transformer on Cortical Surfaces
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    Chapter 43 Accurate Localization of Inner Ear Regions of Interests Using Deep Reinforcement Learning
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    Chapter 44 Shifted Windows Transformers for Medical Image Quality Assessment
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    Chapter 45 Multi-scale Multi-structure Siamese Network (MMSNet) for Primary Open-Angle Glaucoma Prediction
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    Chapter 46 HealNet - Self-supervised Acute Wound Heal-Stage Classification
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    Chapter 47 Federated Tumor Segmentation with Patch-Wise Deep Learning Model
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    Chapter 48 Multi-scale and Focal Region Based Deep Learning Network for Fine Brain Parcellation
Attention for Chapter 6: 3D Segmentation with Fully Trainable Gabor Kernels and Pearson's Correlation Coefficient
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (58th percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

Mentioned by

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Chapter title
3D Segmentation with Fully Trainable Gabor Kernels and Pearson's Correlation Coefficient
Chapter number 6
Book title
Machine Learning in Medical Imaging
Published in
arXiv, December 2022
DOI 10.1007/978-3-031-21014-3_6
Book ISBNs
978-3-03-121013-6, 978-3-03-121014-3
Authors

Ken C. L. Wong, Mehdi Moradi, Wong, Ken C. L., Moradi, Mehdi

View on publisher site
X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 50%
Unknown 2 50%
Readers by discipline Count As %
Computer Science 2 50%
Unknown 2 50%
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 16 December 2022.
All research outputs
#13,866,164
of 23,511,526 outputs
Outputs from arXiv
#236,395
of 972,877 outputs
Outputs of similar age
#175,506
of 442,094 outputs
Outputs of similar age from arXiv
#8,338
of 37,954 outputs
Altmetric has tracked 23,511,526 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 972,877 research outputs from this source. They receive a mean Attention Score of 3.9. This one has gotten more attention than average, scoring higher than 73% 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 442,094 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 58% of its contemporaries.
We're also able to compare this research output to 37,954 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.

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