Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries

Table of Contents

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   Book Overview
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   Chapter 1 Convolutional 3D to 2D Patch Conversion for Pixel-Wise Glioma Segmentation in MRI Scans
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   Chapter 2 TBI Lesion Segmentation in Head CT: Impact of Preprocessing and Data Augmentation
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   Chapter 3 Aneurysm Identification in Cerebral Models with Multiview Convolutional Neural Network
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   Chapter 4 Predicting Clinical Outcome of Stroke Patients with Tractographic Feature
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   Chapter 5 Towards Population-Based Histologic Stain Normalization of Glioblastoma
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   Chapter 6 Skull-Stripping of Glioblastoma MRI Scans Using 3D Deep Learning
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   Chapter 7 Estimation of the Principal Ischaemic Stroke Growth Directions for Predicting Tissue Outcomes
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   Chapter 8 Global and Local Multi-scale Feature Fusion Enhancement for Brain Tumor Segmentation and Pancreas Segmentation
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    Chapter 9 Optimization with Soft Dice Can Lead to a Volumetric Bias
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    Chapter 10 Improved Inter-scanner MS Lesion Segmentation by Adversarial Training on Longitudinal Data
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    Chapter 11 Saliency Based Deep Neural Network for Automatic Detection of Gadolinium-Enhancing Multiple Sclerosis Lesions in Brain MRI
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    Chapter 12 Deep Learning for Brain Tumor Segmentation in Radiosurgery: Prospective Clinical Evaluation
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    Chapter 13 3D U-Net Based Brain Tumor Segmentation and Survival Days Prediction
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    Chapter 14 Aggregating Multi-scale Prediction Based on 3D U-Net in Brain Tumor Segmentation
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    Chapter 15 Brain Tumor Synthetic Segmentation in 3D Multimodal MRI Scans
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    Chapter 16 Multi-step Cascaded Networks for Brain Tumor Segmentation
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    Chapter 17 TuNet: End-to-End Hierarchical Brain Tumor Segmentation Using Cascaded Networks
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    Chapter 18 Using Separated Inputs for Multimodal Brain Tumor Segmentation with 3D U-Net-like Architectures
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    Chapter 19 Two-Step U-Nets for Brain Tumor Segmentation and Random Forest with Radiomics for Survival Time Prediction
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    Chapter 20 Bag of Tricks for 3D MRI Brain Tumor Segmentation
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    Chapter 21 Multi-resolution 3D CNN for MRI Brain Tumor Segmentation and Survival Prediction
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    Chapter 22 Two-Stage Cascaded U-Net: 1st Place Solution to BraTS Challenge 2019 Segmentation Task
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    Chapter 23 Memory-Efficient Cascade 3D U-Net for Brain Tumor Segmentation
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    Chapter 24 A Baseline for Predicting Glioblastoma Patient Survival Time with Classical Statistical Models and Primitive Features Ignoring Image Information
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    Chapter 25 Brain Tumor Segmentation and Survival Prediction Using 3D Attention UNet
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    Chapter 26 Brain Tumor Segmentation Using Dense Channels 2D U-net and Multiple Feature Extraction Network
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    Chapter 27 Brain Tumour Segmentation on MRI Images by Voxel Classification Using Neural Networks, and Patient Survival Prediction
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    Chapter 28 ONCOhabitats Glioma Segmentation Model
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    Chapter 29 Brain Tumor Segmentation with Uncertainty Estimation and Overall Survival Prediction
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    Chapter 30 Cascaded Global Context Convolutional Neural Network for Brain Tumor Segmentation
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    Chapter 31 Multi-task Learning for Brain Tumor Segmentation
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    Chapter 32 Brain Tumor Segmentation and Survival Prediction
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    Chapter 33 Improving Brain Tumor Segmentation with Multi-direction Fusion and Fine Class Prediction
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    Chapter 34 An Ensemble of 2D Convolutional Neural Network for 3D Brain Tumor Segmentation
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    Chapter 35 An Integrative Analysis of Image Segmentation and Survival of Brain Tumour Patients
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    Chapter 36 Triplanar Ensemble of 3D-to-2D CNNs with Label-Uncertainty for Brain Tumor Segmentation
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    Chapter 37 Memory Efficient Brain Tumor Segmentation Using an Autoencoder-Regularized U-Net