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Deep Learning and Data Labeling for Medical Applications

Overview of attention for book
Deep Learning and Data Labeling for Medical Applications
Springer, Cham

Table of Contents

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    Book Overview
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    Chapter 1 HEp-2 Cell Classification Using K-Support Spatial Pooling in Deep CNNs
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    Chapter 2 Robust 3D Organ Localization with Dual Learning Architectures and Fusion
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    Chapter 3 Cell Segmentation Proposal Network for Microscopy Image Analysis
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    Chapter 4 Vessel Detection in Ultrasound Images Using Deep Convolutional Neural Networks
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    Chapter 5 Convolutional Neural Network for Reconstruction of 7T-like Images from 3T MRI Using Appearance and Anatomical Features
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    Chapter 6 Fast Predictive Image Registration
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    Chapter 7 Longitudinal Multiple Sclerosis Lesion Segmentation Using Multi-view Convolutional Neural Networks
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    Chapter 8 Automated Retinopathy of Prematurity Case Detection with Convolutional Neural Networks
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    Chapter 9 Fully Convolutional Network for Liver Segmentation and Lesions Detection
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    Chapter 10 Deep Learning of Brain Lesion Patterns for Predicting Future Disease Activity in Patients with Early Symptoms of Multiple Sclerosis
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    Chapter 11 De-noising of Contrast-Enhanced MRI Sequences by an Ensemble of Expert Deep Neural Networks
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    Chapter 12 Three-Dimensional CT Image Segmentation by Combining 2D Fully Convolutional Network with 3D Majority Voting
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    Chapter 13 Medical Image Description Using Multi-task-loss CNN
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    Chapter 14 Fully Automating Graf’s Method for DDH Diagnosis Using Deep Convolutional Neural Networks
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    Chapter 15 Multi-dimensional Gated Recurrent Units for the Segmentation of Biomedical 3D-Data
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    Chapter 16 Learning Thermal Process Representations for Intraoperative Analysis of Cortical Perfusion During Ischemic Strokes
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    Chapter 17 Automatic Slice Identification in 3D Medical Images with a ConvNet Regressor
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    Chapter 18 Estimating CT Image from MRI Data Using 3D Fully Convolutional Networks
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    Chapter 19 The Importance of Skip Connections in Biomedical Image Segmentation
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    Chapter 20 Understanding the Mechanisms of Deep Transfer Learning for Medical Images
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    Chapter 21 A Region Based Convolutional Network for Tumor Detection and Classification in Breast Mammography
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    Chapter 22 Early Experiences with Crowdsourcing Airway Annotations in Chest CT
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    Chapter 23 Hierarchical Feature Extraction for Nuclear Morphometry-Based Cancer Diagnosis
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    Chapter 24 Using Crowdsourcing for Multi-label Biomedical Compound Figure Annotation
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    Chapter 25 Towards the Semantic Enrichment of Free-Text Annotation of Image Quality Assessment for UK Biobank Cardiac Cine MRI Scans
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    Chapter 26 Focused Proofreading to Reconstruct Neural Connectomes from EM Images at Scale
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    Chapter 27 Hands-Free Segmentation of Medical Volumes via Binary Inputs
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    Chapter 28 Playsourcing: A Novel Concept for Knowledge Creation in Biomedical Research
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    Chapter 29 Erratum to: Automated Retinopathy of Prematurity Case Detection with Convolutional Neural Networks
Overall attention for this book and its chapters
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (97th percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

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