AIMC Topic: Fetal Heart

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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...

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...

Cardiotocography in Obstetrics: New Solutions for "Routine" Technology.

Sensors (Basel, Switzerland)
This work is devoted to the problems of one of the most common screening examinations used in medical practice: fetal cardiotocography (CTG). The technology of ultrasonic monitoring of fetal heart rate (HR) variations has been used for more than 70 y...

Deep Learning-Based Computer-Aided Fetal Echocardiography: Application to Heart Standard View Segmentation for Congenital Heart Defects Detection.

Sensors (Basel, Switzerland)
Accurate segmentation of fetal heart in echocardiography images is essential for detecting the structural abnormalities such as congenital heart defects (CHDs). Due to the wide variations attributed to different factors, such as maternal obesity, abd...

Simultaneous Segmentation of Fetal Hearts and Lungs for Medical Ultrasound Images via an Efficient Multi-scale Model Integrated With Attention Mechanism.

Ultrasonic imaging
Large scale early scanning of fetuses via ultrasound imaging is widely used to alleviate the morbidity or mortality caused by congenital anomalies in fetal hearts and lungs. To reduce the intensive cost during manual recognition of organ regions, man...

Image Segmentation of the Ventricular Septum in Fetal Cardiac Ultrasound Videos Based on Deep Learning Using Time-Series Information.

Biomolecules
Image segmentation is the pixel-by-pixel detection of objects, which is the most challenging but informative in the fundamental tasks of machine learning including image classification and object detection. Pixel-by-pixel segmentation is required to ...

Diagnostic performance of fetal intelligent navigation echocardiography (FINE) in fetuses with double-outlet right ventricle (DORV).

The international journal of cardiovascular imaging
The main objective of this study was to investigate the diagnostic performance of FINE in generating and displaying 3 specific abnormal fetal echocardiography views such as left ventricular outflow tract (LVOT) view, right ventricular outflow tract (...

Hierarchical Class Incremental Learning of Anatomical Structures in Fetal Echocardiography Videos.

IEEE journal of biomedical and health informatics
This paper proposes an ultrasound video interpretation algorithm that enables novel classes or instances to be added over time, without significantly compromising prediction abilities on prior representations. The motivating application is diagnostic...

Machine Learning in Fetal Cardiology: What to Expect.

Fetal diagnosis and therapy
In fetal cardiology, imaging (especially echocardiography) has demonstrated to help in the diagnosis and monitoring of fetuses with a compromised cardiovascular system potentially associated with several fetal conditions. Different ultrasound approac...

DW-Net: A cascaded convolutional neural network for apical four-chamber view segmentation in fetal echocardiography.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Fetal echocardiography (FE) is a widely used medical examination for early diagnosis of congenital heart disease (CHD). The apical four-chamber view (A4C) is an important view among early FE images. Accurate segmentation of crucial anatomical structu...