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Perinatal, Preterm and Paediatric Image Analysis

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Cover of 'Perinatal, Preterm and Paediatric Image Analysis'

Table of Contents

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    Book Overview
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    Chapter 1 FetMRQC: Automated Quality Control for Fetal Brain MRI
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    Chapter 2 A Deep Learning Approach for Segmenting the Subplate and Proliferative Zones in Fetal Brain MRI
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    Chapter 3 Combined Quantitative T2* Map and Structural T2-Weighted Tissue-Specific Analysis for Fetal Brain MRI: Pilot Automated Pipeline
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    Chapter 4 Quantitative T2 Relaxometry in Fetal Brain: Validation Using Modified FaBiaN Fetal Brain MRI Simulator
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    Chapter 5 Towards Automatic Risk Prediction of Coarctation of the Aorta from Fetal CMR Using Atlas-Based Segmentation and Statistical Shape Modelling
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    Chapter 6 The Challenge of Fetal Cardiac MRI Reconstruction Using Deep Learning
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    Chapter 7 Consistency Regularization Improves Placenta Segmentation in Fetal EPI MRI Time Series
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    Chapter 8 Visualization and Quantification of Placental Vasculature Using MRI
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    Chapter 9 The Comparison Analysis of the Cervical Features Between Second-and Third-Trimester Pregnancy in Ultrasound Images Using eXplainable AI
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    Chapter 10 Automatic Infant Respiration Estimation from Video: A Deep Flow-Based Algorithm and a Novel Public Benchmark
Attention for Chapter 4: Quantitative T2 Relaxometry in Fetal Brain: Validation Using Modified FaBiaN Fetal Brain MRI Simulator
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