A Robust Approach Assisted by Signal Quality Assessment for Fetal Heart Rate Estimation from Doppler Ultrasound Signal.

Fetal heart rate (FHR) monitoring, typically using Doppler ultrasound (DUS) signals, is an important technique for assessing fetal health. In this work, we develop a robust DUS-based FHR estimation approach complemented by DUS signal quality assessment (SQA) based on unsupervised representation learning in response to the drawbacks of previous DUS-based FHR estimation and DUS SQA methods. We improve the existing FHR estimation algorithm based on the autocorrelation function (ACF), which is the most widely used method for estimating FHR from DUS signals.

Fetal Heart Rate Detection Using First Derivative of ECG Waveform and Multiple Weighting Functions.

Fetal heart rate monitoring using the abdominal electrocardiograph (ECG) is an important topic for the diagnosis of heart defects. Many studies on fetal heart rate detection have been presented, however, their accuracy is still unsatisfactory. That is because the fetal ECG waveform is contaminated by maternal ECG interference, muscle contractions, and motion artifacts.

Dose reduction in cone-beam CT scanning for intracranial stent deployment before coil embolization of intracranial wide-neck aneurysms.

Purpose: Flat panel detector (FD)-equipped angiography machines are increasingly used for neuro-angiographic imaging. During intracranial stent-assisted coil embolization procedures, it is very important to clearly and quickly visualize stent shape after deployment in the vessel. It is necessary to quickly visualize stents by cone-beam computed tomography (CBCT).