A review on deep-learning algorithms for fetal ultrasound-image analysis
Deep-learning (DL) algorithms are becoming the standard for processing ultrasound (US)
fetal images. A number of survey papers in the field is today available, but most of them are …
fetal images. A number of survey papers in the field is today available, but most of them are …
A review of image processing methods for fetal head and brain analysis in ultrasound images
Background and objective Examination of head shape and brain during the fetal period is
paramount to evaluate head growth, predict neurodevelopment, and to diagnose fetal …
paramount to evaluate head growth, predict neurodevelopment, and to diagnose fetal …
CA-Net: Comprehensive attention convolutional neural networks for explainable medical image segmentation
Accurate medical image segmentation is essential for diagnosis and treatment planning of
diseases. Convolutional Neural Networks (CNNs) have achieved state-of-the-art …
diseases. Convolutional Neural Networks (CNNs) have achieved state-of-the-art …
A new model for brain tumor detection using ensemble transfer learning and quantum variational classifier
J Amin, MA Anjum, M Sharif, S Jabeen… - Computational …, 2022 - Wiley Online Library
A brain tumor is an abnormal enlargement of cells if not properly diagnosed. Early detection
of a brain tumor is critical for clinical practice and survival rates. Brain tumors arise in a …
of a brain tumor is critical for clinical practice and survival rates. Brain tumors arise in a …
Fetal health classification from cardiotocographic data using machine learning
A Mehbodniya, AJP Lazar, J Webber… - Expert …, 2022 - Wiley Online Library
Health complications during the gestation period have evolved as a global issue. These
complications sometimes result in the mortality of the fetus, which is more prevalent in …
complications sometimes result in the mortality of the fetus, which is more prevalent in …
[Retracted] Classification of Alzheimer's Disease Using Gaussian‐Based Bayesian Parameter Optimization for Deep Convolutional LSTM Network
Alzheimer's disease (AD) is one of the most important causes of mortality in elderly people,
and it is often challenging to use traditional manual procedures when diagnosing a disease …
and it is often challenging to use traditional manual procedures when diagnosing a disease …
Deep learning-based computer-aided fetal echocardiography: application to heart standard view segmentation for congenital heart defects detection
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 …
the structural abnormalities such as congenital heart defects (CHDs). Due to the wide …
Automated classification of common maternal fetal ultrasound planes using multi-layer perceptron with deep feature integration
TB Krishna, P Kokil - Biomedical Signal Processing and Control, 2023 - Elsevier
Ultrasound is a standard diagnostic tool used during prenatal care to monitor the growth and
development of the fetus. During routine clinical obstetric examinations, fetal ultrasound …
development of the fetus. During routine clinical obstetric examinations, fetal ultrasound …
Residual attention based uncertainty-guided mean teacher model for semi-supervised breast masses segmentation in 2D ultrasonography
Breast tumor is the second deadliest disease among women around the world. Earlier tumor
diagnosis is extremely important for improving the survival rate. Recent deep-learning …
diagnosis is extremely important for improving the survival rate. Recent deep-learning …
RLDS: An explainable residual learning diagnosis system for fetal congenital heart disease
Fetal congenital heart disease (CHD) is a prevalent and highly complicated fetal deformity.
Furthermore, the number of infants with CHD accounts for as high as 6‰–8‰ among all the …
Furthermore, the number of infants with CHD accounts for as high as 6‰–8‰ among all the …