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Medical Image Understanding and Analysis

Overview of attention for book
Cover of 'Medical Image Understanding and Analysis'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Textural Feature Based Segmentation: A Repeatable and Accurate Segmentation Approach for Tumors in PET Images
  3. Altmetric Badge
    Chapter 2 Unlearning Scanner Bias for MRI Harmonisation in Medical Image Segmentation
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    Chapter 3 Semantic Segmentation of Histopathological Slides for the Classification of Cutaneous Lymphoma and Eczema
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    Chapter 4 Autofocus Net: Auto-focused 3D CNN for Brain Tumour Segmentation
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    Chapter 5 Cortical Plate Segmentation Using CNNs in 3D Fetal Ultrasound
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    Chapter 6 Improving U-Net Segmentation with Active Contour Based Label Correction
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    Chapter 7 Segmenting Hepatocellular Carcinoma in Multi-phase CT
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    Chapter 8 On New Convolutional Neural Network Based Algorithms for Selective Segmentation of Images
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    Chapter 9 Segmentation of the Biliary Tree from MRCP Images via the Monogenic Signal
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    Chapter 10 Transfer Learning for Brain Segmentation: Pre-task Selection and Data Limitations
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    Chapter 11 Pancreas Segmentation-Derived Biomarkers: Volume and Shape Metrics in the UK Biobank Imaging Study
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    Chapter 12 Localization and Identification of Lumbar Intervertebral Discs on Spine MR Images with Faster RCNN Based Shortest Path Algorithm
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    Chapter 13 DeepSplit: Segmentation of Microscopy Images Using Multi-task Convolutional Networks
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    Chapter 14 A Framework for Jointly Assessing and Reducing Imaging Artefacts Automatically Using Texture Analysis and Total Variation Optimisation for Improving Perivascular Spaces Quantification in Brain Magnetic Resonance Imaging
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    Chapter 15 Groupwise Multimodal Image Registration Using Joint Total Variation
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    Chapter 16 CT Scan Registration with 3D Dense Motion Field Estimation Using LSGAN
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    Chapter 17 A Supervised Image Registration Approach for Late Gadolinium Enhanced MRI and Cine Cardiac MRI Using Convolutional Neural Networks
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    Chapter 18 Unsupervised Deep Learning for Stain Separation and Artifact Detection in Histopathology Images
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    Chapter 19 Asymmetric Point Spread Function Estimation and Deconvolution for Serial-Sectioning Block-Face Imaging
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    Chapter 20 Automatic and Objective Facial Palsy Grading Index Prediction Using Deep Feature Regression
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    Chapter 21 Prediction of Thrombectomy Functional Outcomes Using Multimodal Data
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    Chapter 22 Radiomics: A New Biomedical Workflow to Create a Predictive Model
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    Chapter 23 Going Deeper into Cardiac Motion Analysis to Model Fine Spatio-Temporal Features
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    Chapter 24 Ridge Detection and Analysis of Susceptibility-Weighted Magnetic Resonance Imaging in Neonatal Hypoxic-Ischaemic Encephalopathy
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    Chapter 25 A Machine Learning Approach for Colles’ Fracture Treatment Diagnosis
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    Chapter 26 A Lightweight CNN and Joint Shape-Joint Space ($$JS^2$$) Descriptor for Radiological Osteoarthritis Detection
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    Chapter 27 Discovering Unknown Diseases with Explainable Automated Medical Imaging
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    Chapter 28 Investigating Sex Related Phenotype Changes in Knockout Mice by Applying Deep Learning to X-Ray Images
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    Chapter 29 A Deep Learning Approach for Semantic Segmentation of Gonioscopic Images to Support Glaucoma Categorization
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    Chapter 30 A Deep Learning Approach to Detect the Demarcation Line in OCT Images
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    Chapter 31 Retinal Biomarkers Discovery for Cerebral Small Vessel Disease in an Older Population
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    Chapter 32 Simultaneous Optimisation of Confocal and Non-confocal Images in an AOSLO with a Reconfigurable Aperture Pattern
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    Chapter 33 Deep Generative Models to Simulate 2D Patient-Specific Ultrasound Images in Real Time
  35. Altmetric Badge
    Chapter 34 Volumetric Simulation of Nano-Fibres and 2D SEM and 3D XCT Imaging Processes
Attention for Chapter 3: Semantic Segmentation of Histopathological Slides for the Classification of Cutaneous Lymphoma and Eczema
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About this Attention Score

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2 tweeters

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Chapter title
Semantic Segmentation of Histopathological Slides for the Classification of Cutaneous Lymphoma and Eczema
Chapter number 3
Book title
Medical Image Understanding and Analysis
Published in
arXiv, July 2020
DOI 10.1007/978-3-030-52791-4_3
Book ISBNs
978-3-03-052790-7, 978-3-03-052791-4
Authors

Jérémy Scheurer, Claudio Ferrari, Luis Berenguer Todo Bom, Michaela Beer, Werner Kempf, Luis Haug

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 100%
Readers by discipline Count As %
Computer Science 1 100%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 14 September 2020.
All research outputs
#13,335,540
of 17,391,055 outputs
Outputs from arXiv
#322,005
of 696,004 outputs
Outputs of similar age
#203,783
of 293,743 outputs
Outputs of similar age from arXiv
#16,611
of 37,619 outputs
Altmetric has tracked 17,391,055 research outputs across all sources so far. This one is in the 20th percentile – i.e., 20% of other outputs scored the same or lower than it.
So far Altmetric has tracked 696,004 research outputs from this source. They receive a mean Attention Score of 3.9. This one is in the 42nd percentile – i.e., 42% 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 293,743 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 37,619 others from the same source and published within six weeks on either side of this one. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.