AIMC Topic: Ultrasonography, Prenatal
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TKR-FSOD: Fetal Anatomical Structure Few-Shot Detection Utilizing Topological Knowledge Reasoning.
IEEE journal of biomedical and health informatics
Jan 7, 2025
Fetal multi-anatomical structure detection in ultrasound (US) images can clearly present the relationship and influence between anatomical structures, providing more comprehensive information about fetal organ structures and assisting sonographers in...
Latent representation learning for classification of the Doppler ultrasound images.
Computers in biology and medicine
Dec 26, 2024
The classification of Doppler ultrasound images plays an important role in the diagnosis of pregnancy. However, it is a challenging problem that suffers from a variable length of these images with a dimension gap between them. In this study, we propo...
Predicting preterm birth using electronic medical records from multiple prenatal visits.
BMC pregnancy and childbirth
Dec 21, 2024
This study aimed to predict preterm birth in nulliparous women using machine learning and easily accessible variables from prenatal visits. Elastic net regularized logistic regression models were developed and evaluated using 5-fold cross-validation ...
Gestational Age
Cervical Length Measurement
Predictive Value of Tests
Area Under Curve
Adult
Sensitivity and Specificity
Infant, Newborn
Ultrasonography, Prenatal
Premature Birth
Prenatal Care
Young Adult
Risk Assessment
Electronic Health Records
Pregnancy
Female
Logistic Models
Humans
Machine Learning
Cost-effectiveness analysis of AI-based image quality control for perinatal ultrasound screening.
BMC medical education
Dec 18, 2024
PURPOSE: This study aimed to compare the cost-effectiveness of AI-based approaches with manual approaches in ultrasound image quality control (QC).
Novel neural network classification of maternal fetal ultrasound planes through optimized feature selection.
BMC medical imaging
Dec 18, 2024
Ultrasound (US) imaging is an essential diagnostic technique in prenatal care, enabling enhanced surveillance of fetal growth and development. Fetal ultrasonography standard planes are crucial for evaluating fetal development parameters and detecting...
LPC-SonoNet: A Lightweight Network Based on SonoNet and Light Pyramid Convolution for Fetal Ultrasound Standard Plane Detection.
Sensors (Basel, Switzerland)
Nov 25, 2024
The detection of fetal ultrasound standard planes (FUSPs) is important for the diagnosis of fetal malformation and the prevention of perinatal death. As a promising deep-learning technique in FUSP detection, SonoNet's network parameters have a large ...
Application of artificial intelligence in VSD prenatal diagnosis from fetal heart ultrasound images.
BMC pregnancy and childbirth
Nov 16, 2024
BACKGROUND: Developing a combined artificial intelligence (AI) and ultrasound imaging to provide an accurate, objective, and efficient adjunctive diagnostic approach for fetal heart ventricular septal defects (VSD).
Portable ultrasound devices for obstetric care in resource-constrained environments: mapping the landscape.
Gates open research
Oct 29, 2024
BACKGROUND: The WHO's recommendations on antenatal care underscore the need for ultrasound assessment during pregnancy. Given that maternal and perinatal mortality remains unacceptably high in underserved regions, these guidelines are imperative for ...
Fetal Face: Enhancing 3D Ultrasound Imaging by Postprocessing With AI Applications: Myth, Reality, or Legal Concerns?
Journal of clinical ultrasound : JCU
Oct 25, 2024
The use of artificial intelligence (AI) platforms is revolutionizing the performance in managing metadata and big data. Medicine is another field where AI is spreading. However, this technological advancement is not amenable to errors or fraudulent m...
Segmentation of four-chamber view images in fetal ultrasound exams using a novel deep learning model ensemble method.
Computers in biology and medicine
Oct 11, 2024
Fetal echocardiography, a specialized ultrasound application commonly utilized for fetal heart assessment, can greatly benefit from automated segmentation of anatomical structures, aiding operators in their evaluations. We introduce a novel approach ...
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