AIMC Topic: Fetus

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MG-Net: A fetal brain tissue segmentation method based on multiscale feature fusion and graph convolution attention mechanisms.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Fetal brain tissue segmentation provides foundational support for comprehensively understanding the neurodevelopment of normal and congenital disease-affected fetuses. Manual labeling is very time-consuming, and automated se...

Prediction of fetal brain gestational age using multihead attention with Xception.

Computers in biology and medicine
Accurate gestational age (GA) prediction is crucial for monitoring fetal development and ensuring optimal prenatal care. Traditional methods often face challenges in terms of precision and prediction efficiency. In this context, leveraging modern dee...

A novel artificial intelligence model for measuring fetal intracranial markers during the first trimester based on two-dimensional ultrasound image.

International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
OBJECTIVE: To establish reference ranges of fetal intracranial markers during the first trimester and develop the first novel artificial intelligence (AI) model to measure key markers automatically.

FetoML: Interpretable predictions of the fetotoxicity of drugs based on machine learning approaches.

Molecular informatics
Pregnant females may use medications to manage health problems that develop during pregnancy or that they had prior to pregnancy. However, using medications during pregnancy has a potential risk to the fetus. Assessing the fetotoxicity of drugs is es...

Rapid detection of fetal compromise using input length invariant deep learning on fetal heart rate signals.

Scientific reports
Standard clinical practice to assess fetal well-being during labour utilises monitoring of the fetal heart rate (FHR) using cardiotocography. However, visual evaluation of FHR signals can result in subjective interpretations leading to inter and intr...

Investigation on ultrasound images for detection of fetal congenital heart defects.

Biomedical physics & engineering express
Congenital heart defects (CHD) are one of the serious problems that arise during pregnancy. Early CHD detection reduces death rates and morbidity but is hampered by the relatively low detection rates (i.e., 60%) of current screening technology. The d...

PSFHSP-Net: an efficient lightweight network for identifying pubic symphysis-fetal head standard plane from intrapartum ultrasound images.

Medical & biological engineering & computing
The accurate selection of the ultrasound plane for the fetal head and pubic symphysis is critical for precisely measuring the angle of progression. The traditional method depends heavily on sonographers manually selecting the imaging plane. This proc...

Enhancing Fetal Electrocardiogram Signal Extraction Accuracy through a CycleGAN Utilizing Combined CNN-BiLSTM Architecture.

Sensors (Basel, Switzerland)
The fetal electrocardiogram (FECG) records changes in the graph of fetal cardiac action potential during conduction, reflecting the developmental status of the fetus in utero and its physiological cardiac activity. Morphological alterations in the FE...

PSFHS: Intrapartum ultrasound image dataset for AI-based segmentation of pubic symphysis and fetal head.

Scientific data
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...