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Computational Pathology and Ophthalmic Medical Image Analysis

Overview of attention for book
Computational Pathology and Ophthalmic Medical Image Analysis
Springer International Publishing

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Improving Accuracy of Nuclei Segmentation by Reducing Histological Image Variability
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    Chapter 2 Multi-resolution Networks for Semantic Segmentation in Whole Slide Images
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    Chapter 3 Improving High Resolution Histology Image Classification with Deep Spatial Fusion Network
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    Chapter 4 Construction of a Generative Model of H&E Stained Pathology Images of Pancreas Tumors Conditioned by a Voxel Value of MRI Image
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    Chapter 5 Accurate 3D Reconstruction of a Whole Pancreatic Cancer Tumor from Pathology Images with Different Stains
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    Chapter 6 Role of Task Complexity and Training in Crowdsourced Image Annotation
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    Chapter 7 Capturing Global Spatial Context for Accurate Cell Classification in Skin Cancer Histology
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    Chapter 8 Exploiting Multiple Color Representations to Improve Colon Cancer Detection in Whole Slide H&E Stains
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    Chapter 9 Leveraging Unlabeled Whole-Slide-Images for Mitosis Detection
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    Chapter 10 Evaluating Out-of-the-Box Methods for the Classification of Hematopoietic Cells in Images of Stained Bone Marrow
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    Chapter 11 DeepCerv: Deep Neural Network for Segmentation Free Robust Cervical Cell Classification
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    Chapter 12 Whole Slide Image Registration for the Study of Tumor Heterogeneity
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    Chapter 13 Modality Conversion from Pathological Image to Ultrasonic Image Using Convolutional Neural Network
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    Chapter 14 Structure Instance Segmentation in Renal Tissue: A Case Study on Tubular Immune Cell Detection
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    Chapter 15 Cellular Community Detection for Tissue Phenotyping in Histology Images
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    Chapter 16 Automatic Detection of Tumor Budding in Colorectal Carcinoma with Deep Learning
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    Chapter 17 Significance of Hyperparameter Optimization for Metastasis Detection in Breast Histology Images
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    Chapter 18 Image Magnification Regression Using DenseNet for Exploiting Histopathology Open Access Content
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    Chapter 19 Uncertainty Driven Pooling Network for Microvessel Segmentation in Routine Histology Images
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    Chapter 20 Ocular Structures Segmentation from Multi-sequences MRI Using 3D Unet with Fully Connected CRFs
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    Chapter 21 Classification of Findings with Localized Lesions in Fundoscopic Images Using a Regionally Guided CNN
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    Chapter 22 Segmentation of Corneal Nerves Using a U-Net-Based Convolutional Neural Network
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    Chapter 23 Automatic Pigmentation Grading of the Trabecular Meshwork in Gonioscopic Images
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    Chapter 24 Large Receptive Field Fully Convolutional Network for Semantic Segmentation of Retinal Vasculature in Fundus Images
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    Chapter 25 Explaining Convolutional Neural Networks for Area Estimation of Choroidal Neovascularization via Genetic Programming
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    Chapter 26 Joint Segmentation and Uncertainty Visualization of Retinal Layers in Optical Coherence Tomography Images Using Bayesian Deep Learning
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    Chapter 27 cGAN-Based Lacquer Cracks Segmentation in ICGA Image
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    Chapter 28 Localizing Optic Disc and Cup for Glaucoma Screening via Deep Object Detection Networks
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    Chapter 29 Fundus Image Quality-Guided Diabetic Retinopathy Grading
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    Chapter 30 DeepDisc: Optic Disc Segmentation Based on Atrous Convolution and Spatial Pyramid Pooling
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    Chapter 31 Large-Scale Left and Right Eye Classification in Retinal Images
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    Chapter 32 Automatic Segmentation of Cortex and Nucleus in Anterior Segment OCT Images
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    Chapter 33 Local Estimation of the Degree of Optic Disc Swelling from Color Fundus Photography
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    Chapter 34 Visual Field Based Automatic Diagnosis of Glaucoma Using Deep Convolutional Neural Network
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    Chapter 35 Towards Standardization of Retinal Vascular Measurements: On the Effect of Image Centering
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    Chapter 36 Feasibility Study of Subfoveal Choroidal Thickness Changes in Spectral-Domain Optical Coherence Tomography Measurements of Macular Telangiectasia Type 2
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    Chapter 37 Segmentation of Retinal Layers in OCT Images of the Mouse Eye Utilizing Polarization Contrast
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    Chapter 38 Glaucoma Diagnosis from Eye Fundus Images Based on Deep Morphometric Feature Estimation
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    Chapter 39 2D Modeling and Correction of Fan-Beam Scan Geometry in OCT
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    Chapter 40 A Bottom-Up Saliency Estimation Approach for Neonatal Retinal Images
Overall attention for this book and its chapters
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Title
Computational Pathology and Ophthalmic Medical Image Analysis
Published by
Springer International Publishing, December 2018
DOI 10.1007/978-3-030-00949-6
ISBNs
978-3-03-000948-9, 978-3-03-000949-6
Editors

Stoyanov, Danail, Taylor, Zeike, Ciompi, Francesco, Xu, Yanwu, Martel, Anne, Maier-Hein, Lena, Rajpoot, Nasir, van der Laak, Jeroen, Veta, Mitko, McKenna, Stephen, Snead, David, Trucco, Emanuele, Garvin, Mona K., Chen, Xin Jan, Bogunovic, Hrvoje

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The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
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The data shown below were compiled from readership statistics for 66 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Country Count As %
Unknown 66 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 21%
Student > Master 12 18%
Researcher 5 8%
Other 3 5%
Student > Doctoral Student 3 5%
Other 10 15%
Unknown 19 29%
Readers by discipline Count As %
Computer Science 23 35%
Engineering 10 15%
Business, Management and Accounting 2 3%
Agricultural and Biological Sciences 2 3%
Medicine and Dentistry 2 3%
Other 4 6%
Unknown 23 35%