ArticleMedical image analysis2022
Automated 3D reconstruction of the fetal thorax in the standard atlas space from motion-corrupted MRI stacks for 21-36 weeks GA range.
Article in Medical image analysis, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- Automated fetal magnetic resonance imaging lung segmentation for rapid lung volume estimation across diverse pulmonary hypoplasia phenotypes.Pediatric radiology · 2026Article
- Optimization of fetal brain MRI at 0.55 T with slice-to-volume reconstruction.Magma (New York, N.Y.) · 2026Article
- Normative range for MRI amniotic fluid volume from 16 to 36 gestational weeks: Absolute and relative values, and correlation to ultrasound.Acta obstetricia et gynecologica Scandinavica · 2026Observational
- Pulmonary T2* quantification of fetuses with congenital diaphragmatic hernia: a retrospective, case-controlled, MRI pilot study.Pediatric research · 2026Article
- Motion Mitigation Techniques for Abdominal and Cardiac MR Imaging.Journal of magnetic resonance imaging : JMRI · 2026Review
- Fetal Assessment Suite (FetAS): a web-based platform for automatic fetal MRI analysis using AI.Scientific reports · 2025Article
- Artificial Intelligence in Tetralogy of Fallot: From Prenatal Diagnosis to Lifelong Management: A Narrative Review.Bioengineering (Basel, Switzerland) · 2025Review
- Fetal cardiac masses.Pediatric radiology · 2025Review
- Lung volume segmentation in fetal MRI: super-resolution reconstructions improve inter-rater reliability.European radiology experimental · 2025Article
- Fetal Cardiovascular Magnetic Resonance: History, Current Status, and Future Directions.Journal of magnetic resonance imaging : JMRI · 2025Review
- Scanner-based real-time three-dimensional brain + body slice-to-volume reconstruction for T2-weighted 0.55-T low-field fetal magnetic resonance imaging.Pediatric radiology · 2025Article
- The onset of coarctation of the aorta before birth: Mechanistic insights from fetal arch anatomy and haemodynamics.Computers in biology and medicine · 2024Article
- Total and Regional Brain Volumes in Fetuses With Congenital Heart Disease.Journal of magnetic resonance imaging : JMRI · 2024Article
- In vivo T2 measurements of the fetal brain using single-shot fast spin echo sequences.Magnetic resonance in medicine · 2024Article
- Research into super-resolution in medical imaging from 2000 to 2023: bibliometric analysis and visualization.Quantitative imaging in medicine and surgery · 2024Article
- Automated body organ segmentation, volumetry and population-averaged atlas for 3D motion-corrected T2-weighted fetal body MRI.Scientific reports · 2024Article
- Structural and functional fetal cardiac imaging using low field (0.55 T) MRI.Frontiers in pediatrics · 2024Article
- Retrospective motion correction in foetal MRI for clinical applications: existing methods, applications and integration into clinical practice.The British journal of radiology · 2023Review
- Learning the Hidden Signature of Fetal Arch Anatomy: a Three-Dimensional Shape Analysis in Suspected Coarctation of the Aorta.Journal of cardiovascular translational research · 2023Article
- An automated pipeline for quantitative T2* fetal body MRI and segmentation at low field.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2023Article
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10 authors.
Funding
Abstract
Slice-to-volume registration (SVR) methods allow reconstruction of high-resolution 3D images from multiple motion-corrupted stacks. SVR-based pipelines have been increasingly used for motion correction for T2-weighted structural fetal MRI since they allow more informed and detailed diagnosis of brain and body anomalies including congenital heart defects (Lloyd et al., 2019). Recently, fully automated rigid SVR reconstruction of the fetal brain in the atlas space was achieved in Salehi et al. (2019) that used convolutional neural networks (CNNs) for segmentation and pose estimation. However, these CNN-based methods have not yet been applied to the fetal trunk region. Meanwhile, the existing rigid and deformable SVR (DSVR) solutions (Uus et al., 2020) for the fetal trunk region are limited by the requirement of manual input as well the narrow capture range of the classical gradient descent based registration methods that cannot resolve severe fetal motion frequently occurring at the early gestational age (GA). Furthermore, in our experience, the conventional 2D slice-wise CNN-based brain masking solutions are reportedly prone to errors that require manual corrections when applied on a wide range of acquisition protocols or abnormal cases in clinical setting. In this work, we propose a fully automated pipeline for reconstruction of the fetal thorax region for 21-36 weeks GA range T2-weighted MRI datasets. It includes 3D CNN-based intra-uterine localisation of the fetal trunk and landmark-guided pose estimation steps that allow automated DSVR reconstruction in the standard radiological space irrespective of the fetal trunk position or the regional stack coverage. The additional step for generation of the common template space and rejection of outliers provides the means for automated exclusion of stacks affected by low image quality or extreme motion. The pipeline was quantitatively evaluated on a series of experiments including fetal MRI datasets and simulated rotation motion. Furthermore, we performed a qualitative assessment of the image reconstruction quality in terms of the definition of vascular structures on 100 early (median 23.14 weeks) and late (median 31.79 weeks) GA group MRI datasets covering 21 to 36 weeks GA range.
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