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Digital Pathology

Overview of attention for book
Cover of 'Digital Pathology'

Table of Contents

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    Book Overview
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    Chapter 1 Bringing Open Data to Whole Slide Imaging
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    Chapter 2 PanNuke: An Open Pan-Cancer Histology Dataset for Nuclei Instance Segmentation and Classification
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    Chapter 3 Active Learning for Patch-Based Digital Pathology Using Convolutional Neural Networks to Reduce Annotation Costs
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    Chapter 4 Patch Clustering for Representation of Histopathology Images
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    Chapter 5 Virtually Redying Histological Images with Generative Adversarial Networks to Facilitate Unsupervised Segmentation: A Proof-of-Concept Study
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    Chapter 6 Virtualization of Tissue Staining in Digital Pathology Using an Unsupervised Deep Learning Approach
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    Chapter 7 Evaluation of Colour Pre-processing on Patch-Based Classification of H&E-Stained Images
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    Chapter 8 Automated Segmentation of DCIS in Whole Slide Images
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    Chapter 9 A Two-Stage U-Net Algorithm for Segmentation of Nuclei in H&E-Stained Tissues
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    Chapter 10 Automatic Detection of Tumor Buds in Pan-Cytokeratin Stained Colorectal Cancer Sections by a Hybrid Image Analysis Approach
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    Chapter 11 Improving Prostate Cancer Detection with Breast Histopathology Images
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    Chapter 12 Multi-tissue Partitioning for Whole Slide Images of Colorectal Cancer Histopathology Images with Deeptissue Net
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    Chapter 13 Rota-Net: Rotation Equivariant Network for Simultaneous Gland and Lumen Segmentation in Colon Histology Images
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    Chapter 14 Histopathological Image Analysis on Mouse Testes for Automated Staging of Mouse Seminiferous Tubule
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    Chapter 15 Deep Features for Tissue-Fold Detection in Histopathology Images
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    Chapter 16 A Fast Pyramidal Bayesian Model for Mitosis Detection in Whole-Slide Images
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    Chapter 17 Improvement of Mitosis Detection Through the Combination of PHH3 and HE Features
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    Chapter 18 A New Paradigm of RNA-Signal Quantitation and Contextual Visualization for On-Slide Tissue Analysis
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    Chapter 19 Digital Tumor-Collagen Proximity Signature Predicts Survival in Diffuse Large B-Cell Lymphoma
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    Chapter 20 An Integrated Multi-scale Model for Breast Cancer Histopathological Image Classification Using CNN-Pooling and Color-Texture Features
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    Chapter 21 Icytomine: A User-Friendly Tool for Integrating Workflows on Whole Slide Images
Overall attention for this book and its chapters
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Mentioned by

44 tweeters

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Digital Pathology
Published by
Springer International Publishing, September 2019
DOI 10.1007/978-3-030-23937-4
978-3-03-023936-7, 978-3-03-023937-4

Reyes-Aldasoro, Constantino Carlos, Janowczyk, Andrew, Veta, Mitko, Bankhead, Peter, Sirinukunwattana, Korsuk

Twitter Demographics

The data shown below were collected from the profiles of 44 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 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 %
Unspecified 1 25%
Student > Ph. D. Student 1 25%
Unknown 2 50%
Readers by discipline Count As %
Unspecified 1 25%
Computer Science 1 25%
Unknown 2 50%