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OR 2.0 Context-Aware Operating Theaters and Machine Learning in Clinical Neuroimaging

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Cover of 'OR 2.0 Context-Aware Operating Theaters and Machine Learning in Clinical Neuroimaging'

Table of Contents

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    Book Overview
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    Chapter 1 Feature Aggregation Decoder for Segmenting Laparoscopic Scenes
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    Chapter 2 Preoperative Planning for Guidewires Employing Shape-Regularized Segmentation and Optimized Trajectories
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    Chapter 3 Guided Unsupervised Desmoking of Laparoscopic Images Using Cycle-Desmoke
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    Chapter 4 Unsupervised Temporal Video Segmentation as an Auxiliary Task for Predicting the Remaining Surgery Duration
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    Chapter 5 Live Monitoring of Haemodynamic Changes with Multispectral Image Analysis
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    Chapter 6 Towards a Cyber-Physical Systems Based Operating Room of the Future
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    Chapter 7 Deep Transfer Learning for Whole-Brain FMRI Analyses
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    Chapter 8 Knowledge Distillation for Semi-supervised Domain Adaptation
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    Chapter 9 Relevance Vector Machines for Harmonization of MRI Brain Volumes Using Image Descriptors
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    Chapter 10 Data Pooling and Sampling of Heterogeneous Image Data for White Matter Hyperintensity Segmentation
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    Chapter 11 A Hybrid 3DCNN and 3DC-LSTM Based Model for 4D Spatio-Temporal fMRI Data: An ABIDE Autism Classification Study
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    Chapter 12 Automated Quantification of Enlarged Perivascular Spaces in Clinical Brain MRI Across Sites
Attention for Chapter 10: Data Pooling and Sampling of Heterogeneous Image Data for White Matter Hyperintensity Segmentation
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