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Patch-Based Techniques in Medical Imaging

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Cover of 'Patch-Based Techniques in Medical Imaging'

Table of Contents

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    Book Overview
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    Chapter 1 4D Multi-atlas Label Fusion Using Longitudinal Images
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    Chapter 2 Brain Image Labeling Using Multi-atlas Guided 3D Fully Convolutional Networks
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    Chapter 3 Whole Brain Parcellation with Pathology: Validation on Ventriculomegaly Patients
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    Chapter 4 Hippocampus Subfield Segmentation Using a Patch-Based Boosted Ensemble of Autocontext Neural Networks
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    Chapter 5 On the Role of Patch Spaces in Patch-Based Label Fusion
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    Chapter 6 Learning a Sparse Database for Patch-Based Medical Image Segmentation
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    Chapter 7 Accurate and High Throughput Cell Segmentation Method for Mouse Brain Nuclei Using Cascaded Convolutional Neural Network
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    Chapter 8 Learning-Based Estimation of Functional Correlation Tensors in White Matter for Early Diagnosis of Mild Cognitive Impairment
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    Chapter 9 Early Prediction of Alzheimer’s Disease with Non-local Patch-Based Longitudinal Descriptors
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    Chapter 10 Adaptive Fusion of Texture-Based Grading: Application to Alzheimer’s Disease Detection
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    Chapter 11 Micro-CT Guided 3D Reconstruction of Histological Images
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    Chapter 12 A Neural Regression Framework for Low-Dose Coronary CT Angiography (CCTA) Denoising
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    Chapter 13 A Dictionary Learning-Based Fast Imaging Method for Ultrasound Elastography
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    Chapter 14 Breast Tumor Detection in Ultrasound Images Using Deep Learning
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    Chapter 15 Modeling the Intra-class Variability for Liver Lesion Detection Using a Multi-class Patch-Based CNN
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    Chapter 16 Multiple Sclerosis Lesion Segmentation Using Joint Label Fusion
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    Chapter 17 Deep Multimodal Case–Based Retrieval for Large Histopathology Datasets
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    Chapter 18 Sparse Representation Using Block Decomposition for Characterization of Imaging Patterns
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