BACKGROUND: Little research based on the artificial neural network (ANN) is done on preterm birth (spontaneous preterm labor and birth) and its major determinants. This study uses an ANN for analyzing preterm birth and its major determinants.
Human exposure to persistent organic pollutants (POPs) begins during pregnancy and may cause adverse health effects in the fetus or later in life. The present study aimed to assess prenatal POPs exposure to Tanzanian infants and evaluate the distribu...
International journal of computer assisted radiology and surgery
Nov 27, 2018
INTRODUCTION: Twin-to-twin transfusion syndrome (TTTS) is a potentially lethal condition that affects pregnancies in which twins share a single placenta. The definitive treatment for TTTS is fetoscopic laser photocoagulation, a procedure in which pla...
Preeclampsia (PE), new onset hypertension during pregnancy, is associated with a proinflammatory profile compared to normal pregnancy (NP). We hypothesize that CD4 T cells from PE patient placentas cause PE symptoms during pregnancy compared to those...
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Sep 26, 2018
Accurate localization of structural abnormalities is a precursor for image-based prenatal assessment of adverse conditions. For clinical screening and diagnosis of abnormally invasive placenta (AIP), a life-threatening obstetric condition, qualitativ...
We present a new technique to fully automate the segmentation of an organ from 3D ultrasound (3D-US) volumes, using the placenta as the target organ. Image analysis tools to estimate organ volume do exist but are too time consuming and operator depen...
IEEE transactions on pattern analysis and machine intelligence
Jun 1, 2018
Accurate medical image segmentation is essential for diagnosis, surgical planning and many other applications. Convolutional Neural Networks (CNNs) have become the state-of-the-art automatic segmentation methods. However, fully automatic results may ...
Automated literature analysis could significantly speed up understanding of the role of the placenta and the impact of its development and functions on the health of the mother and the child. To facilitate automatic extraction of information about pl...
Quality control (QC) of structures segmentation in volumetric medical images is important for identifying segmentation errors in clinical practice and for facilitating model development by enhancing network performance in semi-supervised and active l...
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