AIMC Topic: Fetus

Clear Filters Showing 71 to 80 of 108 articles

Weakly Supervised Estimation of Shadow Confidence Maps in Fetal Ultrasound Imaging.

IEEE transactions on medical imaging
Detecting acoustic shadows in ultrasound images is important in many clinical and engineering applications. Real-time feedback of acoustic shadows can guide sonographers to a standardized diagnostic viewing plane with minimal artifacts and can provid...

Latent Phase Detection of Hypoxic-Ischemic Spike Transients in the EEG of Preterm Fetal Sheep Using Reverse Biorthogonal Wavelets & Fuzzy Classifier.

International journal of neural systems
Hypoxic-ischemic (HI) studies in preterms lack reliable prognostic biomarkers for diagnostic tests of HI encephalopathy (HIE). Our group's observations from fetal sheep models suggest that potential biomarkers of HIE in the form of developing HI mic...

Multi-task SonoEyeNet: Detection of Fetal Standardized Planes Assisted by Generated Sonographer Attention Maps.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
We present a novel multi-task convolutional neural network called Multi-task SonoEyeNet () that learns to generate clinically relevant visual attention maps using sonographer gaze tracking data on input ultrasound (US) video frames so as to assist st...

Artificial intelligence assistance for fetal head biometry: Assessment of automated measurement software.

Diagnostic and interventional imaging
PURPOSE: To evaluate the feasibility and reproducibility of artificial intelligence software (Smartplanes) to automatically identify the transthalamic plane from 3D ultrasound volumes and to measure the biparietal diameter (BPD) and head circumferenc...

Real-Time Deep Pose Estimation With Geodesic Loss for Image-to-Template Rigid Registration.

IEEE transactions on medical imaging
With an aim to increase the capture range and accelerate the performance of state-of-the-art inter-subject and subject-to-template 3-D rigid registration, we propose deep learning-based methods that are trained to find the 3-D position of arbitrarily...

Fetal health status prediction based on maternal clinical history using machine learning techniques.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Congenital anomalies are seen at 1-3% of the population, probabilities of which are tried to be found out primarily through double, triple and quad tests during pregnancy. Also, ultrasonographical evaluations of fetuses enha...

A metabolomics-based approach for non-invasive screening of fetal central nervous system anomalies.

Metabolomics : Official journal of the Metabolomic Society
BACKGROUND: Central nervous system anomalies represent a wide range of congenital birth defects, with an incidence of approximately 1% of all births. They are currently diagnosed using ultrasound evaluation. However, there is strong need for a more a...

A Crossover Comparison of Standard and Telerobotic Approaches to Prenatal Sonography.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
OBJECTIVES: To determine the feasibility of a telerobotic approach to remotely perform prenatal sonographic examinations.

A deep learning approach for fetal QRS complex detection.

Physiological measurement
OBJECTIVE: Non-invasive foetal electrocardiography (NI-FECG) has the potential to provide more additional clinical information for detecting and diagnosing fetal diseases. We propose and demonstrate a deep learning approach for fetal QRS complex dete...

Development of A Machine Learning Algorithm to Classify Drugs Of Unknown Fetal Effect.

Scientific reports
Many drugs commonly prescribed during pregnancy lack a fetal safety recommendation - called FDA 'category C' drugs. This study aims to classify these drugs into harmful and safe categories using knowledge gained from chemoinformatics (i.e., pharmacol...