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ISBI 2019 C-NMC Challenge: Classification in Cancer Cell Imaging

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Cover of 'ISBI 2019 C-NMC Challenge: Classification in Cancer Cell Imaging'

Table of Contents

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    Book Overview
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    Chapter 1 Classification of Normal Versus Malignant Cells in B-ALL White Blood Cancer Microscopic Images
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    Chapter 2 Classification of Leukemic B-Lymphoblast Cells from Blood Smear Microscopic Images with an Attention-Based Deep Learning Method and Advanced Augmentation Techniques
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    Chapter 3 Classification of Normal and Leukemic Blast Cells in B-ALL Cancer Using a Combination of Convolutional and Recurrent Neural Networks
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    Chapter 4 Deep Learning for Classifying of White Blood Cancer
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    Chapter 5 Ensemble Convolutional Neural Networks for Cell Classification in Microscopic Images
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    Chapter 6 Acute Lymphoblastic Leukemia Classification from Microscopic Images Using Convolutional Neural Networks
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    Chapter 7 Toward Automated Classification of B-Acute Lymphoblastic Leukemia
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    Chapter 8 Neighborhood-Correction Algorithm for Classification of Normal and Malignant Cells
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    Chapter 9 DeepMEN: Multi-model Ensemble Network for B-Lymphoblast Cell Classification
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    Chapter 10 Multi-streams and Multi-features for Cell Classification
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    Chapter 11 Classification of Normal Versus Malignant Cells in B-ALL Microscopic Images Based on a Tiled Convolution Neural Network Approach
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    Chapter 12 Acute Lymphoblastic Leukemia Cells Image Analysis with Deep Bagging Ensemble Learning
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    Chapter 13 Leukemic B-Lymphoblast Cell Detection with Monte Carlo Dropout Ensemble Models
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    Chapter 14 ISBI Challenge 2019: Convolution Neural Networks for B-ALL Cell Classification
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    Chapter 15 Classification of Cancer Microscopic Images via Convolutional Neural Networks
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