Intro
Preface
Organization
Contents
Fetal Brain Image Analysis
FetMRQC: Automated Quality Control for Fetal Brain MRI
1 Introduction
2 Methodology
2.1 Data
2.2 Manual QA of Fetal MRI Stacks
2.3 IQMs Extraction and Learning
3 Results and Discussion
4 Conclusion
References
A Deep Learning Approach for Segmenting the Subplate and Proliferative Zones in Fetal Brain MRI
1 Introduction
2 Methods
2.1 Cohort, Datasets and Preprocessing
2.2 Neuroanatomical Parcellation of Transient Regions
2.3 Automated Segmentation of Transient Regions

2.4 Qualitative and Quantitative Analyses of Transient Regions
3 Results and Discussion
3.1 Qualitative Analysis of Transient Regions in Atlas Space
3.2 Quantitative Analyses of Transient Regions in Subject Space
3.3 Quantitative Comparison of Transient Volumes in Fetuses with Ventriculomegaly and Controls
4 Conclusion and Future Work
References
Combined Quantitative T2* Map and Structural T2-Weighted Tissue-Specific Analysis for Fetal Brain MRI: Pilot Automated Pipeline
1 Introduction
2 Methods
2.1 Datasets, Acquisition and Pre-processing

2.2 Automated 3D T2* Fetal Brain Reconstruction in T2w Space
2.3 Automated 3D T2* Fetal Brain Tissue Segmentation
2.4 Analysis of Brain Development in Combined T2w+T2* Datasets
2.5 Implementation Details
3 Experiments and Results
3.1 Automated 3D T2* Fetal Brain Reconstruction in T2w Space
3.2 Automated 3D T2* Fetal Brain Tissue Segmentation
3.3 Analysis of Brain Development in T2w+T2* Datasets
4 Discussion and Conclusions
References
Quantitative T2 Relaxometry in Fetal Brain: Validation Using Modified FaBiaN Fetal Brain MRI Simulator
1 Introduction

2 Methodology
2.1 Quantitative T2 Measurement Framework for Fetal MRI
2.2 Overview of the FaBiAN Phantom
2.3 The Fetal Brain Model
2.4 Modelling Fetal Motion
2.5 Modelling Signals with Slice Profiles
2.6 Sampling K-Space
2.7 Modelling the Signals for the Dictionary
2.8 Simulated Experiments
2.9 Fetal Brain Measurements
3 Results
3.1 Simulated Fetal MRI
3.2 Reconstruction of T2 Maps from Simulated Fetal Data
3.3 Fetal Measurements
4 Discussion
5 Conclusion
References
Fetal Cardiac Image Analysis

Towards Automatic Risk Prediction of Coarctation of the Aorta from Fetal CMR Using Atlas-Based Segmentation and Statistical Shape Modelling
1 Introduction
1.1 Contributions
2 Methods
2.1 Dataset Description
2.2 Automated Segmentation
2.3 Statistical Shape Analysis
3 Results
3.1 Segmentation
3.2 Statistical Shape Analysis
4 Discussion
5 Conclusion
References
The Challenge of Fetal Cardiac MRI Reconstruction Using Deep Learning
1 Introduction
2 Methods
3 Results
4 Discussion
5 Conclusion
References
Placental and Cervical Image Analysis