AIMC Topic: Ultrasonography, Prenatal

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Fetal electrocardiography and artificial intelligence for prenatal detection of congenital heart disease.

Acta obstetricia et gynecologica Scandinavica
INTRODUCTION: This study aims to investigate non-invasive electrocardiography as a method for the detection of congenital heart disease (CHD) with the help of artificial intelligence.

Use of artificial intelligence and deep learning in fetal ultrasound imaging.

Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology
Deep learning is considered the leading artificial intelligence tool in image analysis in general. Deep-learning algorithms excel at image recognition, which makes them valuable in medical imaging. Obstetric ultrasound has become the gold standard im...

Combining deep learning and intelligent biometry to extract ultrasound standard planes and assess early gestational weeks.

European radiology
OBJECTIVES: To develop and validate a fully automated AI system to extract standard planes, assess early gestational weeks, and compare the performance of the developed system to sonographers.

Simulator, machine learning, and artificial intelligence: Time has come to assist prenatal ultrasound diagnosis.

Journal of clinical ultrasound : JCU
In this Commentary authors investigated and extended the role of simulator in assisting obstetric sonographers in training program. The interconnection of different digitalized technologies such as digital data, artificial neuronal and convolutional ...

Classification of normal and abnormal fetal heart ultrasound images and identification of ventricular septal defects based on deep learning.

Journal of perinatal medicine
OBJECTIVES: Congenital heart defects (CHDs) are the most common birth defects. Recently, artificial intelligence (AI) was used to assist in CHD diagnosis. No comparison has been made among the various types of algorithms that can assist in the prenat...

Fetal brain activity and the free energy principle.

Journal of perinatal medicine
OBJECTIVES: To study whether the free energy principle can explain fetal brain activity and the existence of fetal consciousness via a chaotic dimension derived using artificial intelligence.

Domain-guided data augmentation for deep learning on medical imaging.

PloS one
While domain-specific data augmentation can be useful in training neural networks for medical imaging tasks, such techniques have not been widely used to date. Our objective was to test whether domain-specific data augmentation is useful for medical ...

Multi-centre deep learning for placenta segmentation in obstetric ultrasound with multi-observer and cross-country generalization.

Scientific reports
The placenta is crucial to fetal well-being and it plays a significant role in the pathogenesis of hypertensive pregnancy disorders. Moreover, a timely diagnosis of placenta previa may save lives. Ultrasound is the primary imaging modality in pregnan...

Application of Artificial Intelligence in Anatomical Structure Recognition of Standard Section of Fetal Heart.

Computational and mathematical methods in medicine
Congenital heart defect (CHD) refers to the overall structural abnormality of the heart or large blood vessels in the chest cavity. It is the most common type of fetal congenital defects. Prenatal diagnosis of congenital heart disease can improve the...