AIMC Topic: Ultrasonography, Prenatal
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HFSCCD: A Hybrid Neural Network for Fetal Standard Cardiac Cycle Detection in Ultrasound Videos.
IEEE journal of biomedical and health informatics
May 6, 2024
In the fetal cardiac ultrasound examination, standard cardiac cycle (SCC) recognition is the essential foundation for diagnosing congenital heart disease. Previous studies have mostly focused on the detection of adult CCs, which may not be applicable...
PSFHS: Intrapartum ultrasound image dataset for AI-based segmentation of pubic symphysis and fetal head.
Scientific data
May 2, 2024
During the process of labor, the intrapartum transperineal ultrasound examination serves as a valuable tool, allowing direct observation of the relative positional relationship between the pubic symphysis and fetal head (PSFH). Accurate assessment of...
Deep learning prediction of renal anomalies for prenatal ultrasound diagnosis.
Scientific reports
Apr 19, 2024
Deep learning algorithms have demonstrated remarkable potential in clinical diagnostics, particularly in the field of medical imaging. In this study, we investigated the application of deep learning models in early detection of fetal kidney anomalies...
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 ...
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