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Related papers: An automated pipeline for quantitative T2* fetal b…

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Relaxometry studies in preterm and at-term newborns have provided insight into brain microstructure, thus opening new avenues for studying normal brain development and supporting diagnosis in equivocal neurological situations. However, such…

The automatic segmentation of perinatal brain structures in magnetic resonance imaging (MRI) is of utmost importance for the study of brain growth and related complications. While different methods exist for adult and pediatric MRI data,…

Purpose: To develop a MRI acquisition and reconstruction framework for volumetric cine visualisation of the fetal heart and great vessels in the presence of maternal and fetal motion. Methods: Four-dimensional depiction was achieved using a…

Purpose: This work aims to enable real-time automated intra-uterine volumetric reporting and fetal weight estimation for fetal MRI, deployed directly on the scanner. Methods: A multi-region segmentation nnUNet was trained on 146 bSSFP…

Purpose: To provide real-time quantitative organ-specific information - specifically placental and brain T2* - to allow optimization of the MR examination to the individual patient. Methods: A FIRE-based real-time setup segmenting placenta…

T2 mapping in fetal brain MRI has the potential to improve characterization of the developing brain, especially at mid-field (0.55T), where T2 decay is slower. However, this is challenging as fetal MRI acquisition relies on multiple…

Quantitative analysis of in utero human brain development is crucial for abnormal characterization. Magnetic resonance image (MRI) segmentation is therefore an asset for quantitative analysis. However, the development of automated…

Image and Video Processing · Electrical Eng. & Systems 2024-10-28 Priscille de Dumast , Meritxell Bach Cuadra

The development of automated tools for brain morphometric analysis in infants has lagged significantly behind analogous tools for adults. This gap reflects the greater challenges in this domain due to: 1) a smaller-scaled region of…

Image and Video Processing · Electrical Eng. & Systems 2020-05-21 Lilla Zöllei , Juan Eugenio Iglesias , Yangming Ou , P. Ellen Grant , Bruce Fischl

Fetal lung maturity is a critical indicator for predicting neonatal outcomes and the need for post-natal intervention, especially for pregnancies affected by fetal growth restriction. Intra-voxel incoherent motion analysis has shown…

Computer Vision and Pattern Recognition · Computer Science 2025-07-18 Zhennan Xiao , Katharine Brudkiewicz , Zhen Yuan , Rosalind Aughwane , Magdalena Sokolska , Joanna Chappell , Trevor Gaunt , Anna L. David , Andrew P. King , Andrew Melbourne

Fetal brain magnetic resonance imaging (MRI) is crucial for assessing neurodevelopment in utero. However, fetal MRI analysis remains technically challenging due to fetal motion, low signal-to-noise ratio, and the need for complex multi-step…

Resting-state functional Magnetic Resonance Imaging (fMRI) is a powerful imaging technique for studying functional development of the brain in utero. However, unpredictable and excessive movement of fetuses has limited clinical application…

Multi-slice magnetic resonance images of the fetal brain are usually contaminated by severe and arbitrary fetal and maternal motion. Hence, stable and robust motion correction is necessary to reconstruct high-resolution 3D fetal brain…

Image and Video Processing · Electrical Eng. & Systems 2022-09-23 Wen Shi , Haoan Xu , Cong Sun , Jiwei Sun , Yamin Li , Xinyi Xu , Tianshu Zheng , Yi Zhang , Guangbin Wang , Dan Wu

Purpose: Identification of abdominal Lymph Nodes (LN) that are suspicious for metastasis in T2 Magnetic Resonance Imaging (MRI) scans is critical for staging of lymphoproliferative diseases. Prior work on LN detection has been limited to…

Image and Video Processing · Electrical Eng. & Systems 2022-04-05 Tejas Sudharshan Mathai , Sungwon Lee , Thomas C. Shen , Zhiyong Lu , Ronald M. Summers

Organoids are self-organized 3D cell clusters that closely mimic the architecture and function of in vivo tissues and organs. Quantification of organoid morphology helps in studying organ development, drug discovery, and toxicity…

Image and Video Processing · Electrical Eng. & Systems 2024-04-09 Xiaodan Xing , Chunling Tang , Yunzhe Guo , Nicholas Kurniawan , Guang Yang

The fetal cortical plate undergoes drastic morphological changes throughout early in utero development that can be observed using magnetic resonance (MR) imaging. An accurate MR image segmentation, and more importantly a topologically…

Image and Video Processing · Electrical Eng. & Systems 2024-10-30 Priscille de Dumast , Hamza Kebiri , Chirine Atat , Vincent Dunet , Mériam Koob , Meritxell Bach Cuadra

Resting-state functional Magnetic Resonance Imaging (fMRI) is a powerful imaging technique for studying functional development of the brain in utero. However, unpredictable and excessive movement of fetuses have limited its clinical…

Dynamic free-breathing fetal cardiac MRI is one of the most challenging modalities, which requires high temporal and spatial resolution to depict rapid changes in a small fetal heart. The ability of deep learning methods to recover…

Image and Video Processing · Electrical Eng. & Systems 2023-08-16 Denis Prokopenko , Kerstin Hammernik , Thomas Roberts , David F A Lloyd , Daniel Rueckert , Joseph V Hajnal

Monitoring maternal and fetal health during pregnancy is crucial for preventing adverse outcomes. While tests such as ultrasound scans offer high accuracy, they can be costly and inconvenient. Telehealth and more accessible body shape…

Purpose: A combined diffusion-relaxometry MR acquisition and analysis pipeline for in-vivo human placenta, which allows for exploration of coupling between T2* and apparent diffusion coefficient (ADC) measurements in a sub 10 minute scan…

Deep learning approaches have achieved state-of-the-art performance in cardiac magnetic resonance (CMR) image segmentation. However, most approaches have focused on learning image intensity features for segmentation, whereas the…

Computer Vision and Pattern Recognition · Computer Science 2019-07-16 Jinming Duan , Ghalib Bello , Jo Schlemper , Wenjia Bai , Timothy J W Dawes , Carlo Biffi , Antonio de Marvao , Georgia Doumou , Declan P O'Regan , Daniel Rueckert
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