Journal ArticleDOI
Segmentation and classification in MRI and US fetal imaging: Recent trends and future prospects.
Jordina Torrents-Barrena,Gemma Piella,Narcís Masoller,Eduard Gratacós,Elisenda Eixarch,Mario Ceresa,Miguel Ángel González Ballester +6 more
TLDR
This review covers state‐of‐the‐art segmentation and classification methodologies for the whole fetus and, more specifically, the fetal brain, lungs, liver, heart and placenta in magnetic resonance imaging and (3D) ultrasound for the first time.About:
This article is published in Medical Image Analysis.The article was published on 2019-01-01. It has received 70 citations till now.read more
Citations
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Journal ArticleDOI
Automatic linear measurements of the fetal brain on MRI with deep neural networks
Netanell Avisdris,Netanell Avisdris,Bossmat Yehuda,Bossmat Yehuda,Ori Ben-Zvi,Ori Ben-Zvi,Daphna Link-Sourani,Liat Ben-Sira,Liat Ben-Sira,Elka Miller,Elena Zharkov,Dafna Ben-Bashat,Dafna Ben-Bashat,Leo Joskowicz +13 more
TL;DR: In this article, the authors developed a fully automatic method for computing the cerebral biparietal diameter (CBD) and trans-cerebellum diameter (TCD) measurements from fetal brain MRI.
Posted Content
Hybrid Attention for Automatic Segmentation of Whole Fetal Head in Prenatal Ultrasound Volumes
TL;DR: This paper proposes the first fully-automated solution to segment the whole fetal head in US volumes and is promising to be a feasible solution in assisting the volumetric US-based prenatal studies.
Journal ArticleDOI
Hybrid attention for automatic segmentation of whole fetal head in prenatal ultrasound volumes.
TL;DR: Wang et al. as discussed by the authors proposed a hybrid attention scheme (HAS) to select discriminative features and suppress the non-informative volumetric features in a composite and hierarchical way.
Guided Random Forests for identification of key fetal anatomy and image categorization in ultrasound scans
TL;DR: A novel machine learning based method to categorize unlabeled fetal ultrasound images that utilizes a translation and orientation invariant feature which captures the appearance of a region at multiple spatial resolutions is proposed.
Journal ArticleDOI
Recognition of Fetal Facial Ultrasound Standard Plane Based on Texture Feature Fusion.
TL;DR: Wang et al. as discussed by the authors proposed a texture feature fusion method (LH-SVM) for automatic recognition and classification of fetal facial ultrasound standard plane (FFUSP) for accurate facial deformity detection and disease screening, such as cleft lip and palate detection and Down syndrome screening check.
References
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Journal ArticleDOI
Efficient Multi-Scale 3D CNN with Fully Connected CRF for Accurate Brain Lesion Segmentation
Konstantinos Kamnitsas,Christian Ledig,Virginia F. J. Newcombe,Joanna P. Simpson,Andrew D. Kane,David K. Menon,Daniel Rueckert,Ben Glocker +7 more
TL;DR: An efficient and effective dense training scheme which joins the processing of adjacent image patches into one pass through the network while automatically adapting to the inherent class imbalance present in the data, and improves on the state-of-the‐art for all three applications.
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A Randomized Trial of Prenatal versus Postnatal Repair of Myelomeningocele
N. Scott Adzick,Elizabeth Thom,Catherine Y. Spong,John W. Brock,Pamela K. Burrows,Mark P. Johnson,Lori J. Howell,Jody A. Farrell,Mary E. Dabrowiak,Leslie N. Sutton,Nalin Gupta,Noel Tulipan,Diana L. Farmer +12 more
TL;DR: Prenatal surgery for myelomeningocele reduced the need for shunting and improved motor outcomes at 30 months but was associated with maternal and fetal risks and increased risk of preterm delivery and uterine dehiscence at delivery.
Journal ArticleDOI
Interactive Medical Image Segmentation Using Deep Learning With Image-Specific Fine Tuning
Guotai Wang,Wenqi Li,Maria A. Zuluaga,Rosalind Pratt,Premal A. Patel,Michael Aertsen,Tom Doel,Anna L. David,Jan Deprest,Sebastien Ourselin,Tom Vercauteren +10 more
TL;DR: A novel deep learning-based interactive segmentation framework by incorporating CNNs into a bounding box and scribble-based segmentation pipeline and proposing a weighted loss function considering network and interaction-based uncertainty for the fine tuning is proposed.
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The ultrasonic changes in the maturing placenta and their relation to fetal pulmonic maturity.
TL;DR: A correlation between maturational changes of the placenta as seen by ultrasound and fetal pulmonic maturity as indicated by L/S ratio is suggested.