AIMC Topic: Ultrasonography, Prenatal
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A deep learning framework for identifying and segmenting three vessels in fetal heart ultrasound images.
Biomedical engineering online
Apr 2, 2024
BACKGROUND: Congenital heart disease (CHD) is one of the most common birth defects in the world. It is the leading cause of infant mortality, necessitating an early diagnosis for timely intervention. Prenatal screening using ultrasound is the primary...
Deep-learning computer vision can identify increased nuchal translucency in the first trimester of pregnancy.
Prenatal diagnosis
Apr 1, 2024
OBJECTIVE: Many fetal anomalies can already be diagnosed by ultrasound in the first trimester of pregnancy. Unfortunately, in clinical practice, detection rates for anomalies in early pregnancy remain low. Our aim was to use an automated image segmen...
Artificial Intelligence in Imaging in the First Trimester of Pregnancy: A Systematic Review.
Fetal diagnosis and therapy
Mar 18, 2024
INTRODUCTION: Ultrasonography in the first trimester of pregnancy offers an early screening tool to identify high risk pregnancies. Artificial intelligence (AI) algorithms have the potential to improve the accuracy of diagnosis and assist the clinici...
Artificial intelligence assistance for fetal development: evaluation of an automated software for biometry measurements in the mid-trimester.
BMC pregnancy and childbirth
Feb 23, 2024
BACKGROUND: This study presents CUPID, an advanced automated measurement software based on Artificial Intelligence (AI), designed to evaluate nine fetal biometric parameters in the mid-trimester. Our primary objective was to assess and compare the CU...
Pattern Recognition and Anomaly Detection in fetal morphology using Deep Learning and Statistical learning (PARADISE): protocol for the development of an intelligent decision support system using fetal morphology ultrasound scan to detect fetal congenital anomaly detection.
BMJ open
Feb 15, 2024
INTRODUCTION: Congenital anomalies are the most encountered cause of fetal death, infant mortality and morbidity. 7.9 million infants are born with congenital anomalies yearly. Early detection of congenital anomalies facilitates life-saving treatment...
Artificial Intelligence to Determine Fetal Sex.
American journal of perinatology
Feb 9, 2024
OBJECTIVE: This proof-of-concept study assessed how confidently an artificial intelligence (AI) model can determine the sex of a fetus from an ultrasound image.
Advances in the Application of Artificial Intelligence in Fetal Echocardiography.
Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography
Jan 9, 2024
Congenital heart disease is a severe health risk for newborns. Early detection of abnormalities in fetal cardiac structure and function during pregnancy can help patients seek timely diagnostic and therapeutic advice, and early intervention planning ...
Deep learning to estimate gestational age from fly-to cineloop videos: A novel approach to ultrasound quality control.
International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
Jan 8, 2024
OBJECTIVE: Low-cost devices have made obstetric sonography possible in settings where it was previously unfeasible, but ensuring quality and consistency at scale remains a challenge. In the present study, we sought to create a tool to reduce substand...
Deep learning algorithm for predicting preterm birth in the case of threatened preterm labor admissions using transvaginal ultrasound.
Journal of medical ultrasonics (2001)
Dec 15, 2023
PURPOSE: Preterm birth presents a major challenge in perinatal care, and predicting preterm birth remains a major challenge. If preterm birth cases can be accurately predicted during pregnancy, preventive interventions and more intensive prenatal mon...
Transfer learning for accurate fetal organ classification from ultrasound images: a potential tool for maternal healthcare providers.
Scientific reports
Oct 20, 2023
Ultrasound imaging is commonly used to aid in fetal development. It has the advantage of being real-time, low-cost, non-invasive, and easy to use. However, fetal organ detection is a challenging task for obstetricians, it depends on several factors, ...
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