AIMC Topic: Fetus
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Enhancing Fetal Electrocardiogram Signal Extraction Accuracy through a CycleGAN Utilizing Combined CNN-BiLSTM Architecture.
Sensors (Basel, Switzerland)
May 6, 2024
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
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 microstructure estimation of developing brains from diffusion MRI: A newborn and fetal study.
Medical image analysis
Apr 25, 2024
Diffusion-weighted magnetic resonance imaging (dMRI) is widely used to assess the brain white matter. Fiber orientation distribution functions (FODs) are a common way of representing the orientation and density of white matter fibers. However, with s...
Autonomous fetal morphology scan: deep learning + clustering merger - the second pair of eyes behind the doctor.
BMC medical informatics and decision making
Apr 19, 2024
The main cause of fetal death, of infant morbidity or mortality during childhood years is attributed to congenital anomalies. They can be detected through a fetal morphology scan. An experienced sonographer (with more than 2000 performed scans) has t...
A Dempster-Shafer Approach to Trustworthy AI With Application to Fetal Brain MRI Segmentation.
IEEE transactions on pattern analysis and machine intelligence
Apr 3, 2024
Deep learning models for medical image segmentation can fail unexpectedly and spectacularly for pathological cases and images acquired at different centers than training images, with labeling errors that violate expert knowledge. Such errors undermin...
Application of artificial neural networks to evaluate femur development in the human fetus.
PloS one
Mar 13, 2024
The present article concentrates on an innovative analysis that was performed to assess the development of the femur in human fetuses using artificial intelligence. As a prerequisite, linear dimensions, cross-sectional surface areas and volumes of th...
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...
Multichannel high noise level ECG denoising based on adversarial deep learning.
Scientific reports
Jan 8, 2024
This paper proposes a denoising method based on an adversarial deep learning approach for the post-processing of multi-channel fetal electrocardiogram (ECG) signals. As it's well known, noise leads to misinterpretations of fetal ECG signals and thus ...
Deep learning-based segmentation of whole-body fetal MRI and fetal weight estimation: assessing performance, repeatability, and reproducibility.
European radiology
Sep 2, 2023
OBJECTIVES: To develop a deep-learning method for whole-body fetal segmentation based on MRI; to assess the method's repeatability, reproducibility, and accuracy; to create an MRI-based normal fetal weight growth chart; and to assess the sensitivity ...
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