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Radiomics and Radiogenomics in Neuro-oncology

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Cover of 'Radiomics and Radiogenomics in Neuro-oncology'

Table of Contents

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    Book Overview
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    Chapter 1 Current Status of the Use of Machine Learning and Magnetic Resonance Imaging in the Field of Neuro-Radiomics
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    Chapter 2 Opportunities and Advances in Radiomics and Radiogenomics in Neuro-Oncology
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    Chapter 3 A Survey on Recent Advancements for AI Enabled Radiomics in Neuro-Oncology
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    Chapter 4 Deep Radiomic Features from MRI Scans Predict Survival Outcome of Recurrent Glioblastoma
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    Chapter 5 cuRadiomics: A GPU-Based Radiomics Feature Extraction Toolkit
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    Chapter 6 On Validating Multimodal MRI Based Stratification of IDH Genotype in High Grade Gliomas Using CNNs and Its Comparison to Radiomics
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    Chapter 7 Imaging Signature of 1p/19q Co-deletion Status Derived via Machine Learning in Lower Grade Glioma
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    Chapter 8 A Feature-Pooling and Signature-Pooling Method for Feature Selection for Quantitative Image Analysis: Application to a Radiomics Model for Survival in Glioma
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    Chapter 9 Radiomics-Enhanced Multi-task Neural Network for Non-invasive Glioma Subtyping and Segmentation
Attention for Chapter 8: A Feature-Pooling and Signature-Pooling Method for Feature Selection for Quantitative Image Analysis: Application to a Radiomics Model for Survival in Glioma
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