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Arteries

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Deep learning for artery-vein classification in optical coherence tomography angiography.

Experimental biology and medicine (Maywood, N.J.)
Major retinopathies can differentially impact the arteries and veins. Traditional fundus photography provides limited resolution for visualizing retinal vascular details. Optical coherence tomography (OCT) can provide improved resolution for retinal ...

Non-invasive arterial blood pressure measurement and SpO estimation using PPG signal: a deep learning framework.

BMC medical informatics and decision making
BACKGROUND: Monitoring blood pressure and peripheral capillary oxygen saturation plays a crucial role in healthcare management for patients with chronic diseases, especially hypertension and vascular disease. However, current blood pressure measureme...

Transformer-based deep learning denoising of single and multi-delay 3D arterial spin labeling.

Magnetic resonance in medicine
PURPOSE: To present a Swin Transformer-based deep learning (DL) model (SwinIR) for denoising single-delay and multi-delay 3D arterial spin labeling (ASL) and compare its performance with convolutional neural network (CNN) and other Transformer-based ...

Examining arterial pulsation to identify and risk-stratify heart failure subjects with deep neural network.

Physical and engineering sciences in medicine
Hemodynamic parameters derived from pulse wave analysis have been shown to predict long-term outcomes in patients with heart failure (HF). Here we aimed to develop a deep-learning based algorithm that incorporates pressure waveforms for the identific...

Thrombosed Persistent Median Artery with Coexisting Bifid Median Nerve in a Robotic Arthroplasty Surgeon: A Case Report.

JBJS case connector
CASE: A 47-year-old orthopaedic surgeon presented with acute volar left wrist pain. He performed over 250 robot-assisted knee arthroplasties each year. Color Doppler evaluation revealed bilateral persistent median arteries and bifid median nerves, wi...

Dark-Blood Computed Tomography Angiography Combined With Deep Learning Reconstruction for Cervical Artery Wall Imaging in Takayasu Arteritis.

Korean journal of radiology
OBJECTIVE: To evaluate the image quality of novel dark-blood computed tomography angiography (CTA) imaging combined with deep learning reconstruction (DLR) compared to delayed-phase CTA images with hybrid iterative reconstruction (HIR), to visualize ...

Arterial Diameter Trend Estimation Using Deep Learning on Ultrasound Spectral Doppler.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This study presents an approach for estimating gaps in arterial diameter using flow velocity obtained from spectral Doppler data. We utilize short-time Fourier transform in conjunction with deep learning models designed for spectrograms to estimate a...

Physics-Informed Graph Neural Networks to solve 1-D equations of blood flow.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Computational models of hemodynamics can contribute to optimizing surgical plans, and improve our understanding of cardiovascular diseases. Recently, machine learning methods have become essential to reduce the computational...

A machine learning based algorithm accurately stages liver disease by quantification of arteries.

Scientific reports
A major histologic feature of cirrhosis is the loss of liver architecture with collapse of tissue and vascular changes per unit. We developed qVessel to quantify the arterial density (AD) in liver biopsies with chronic disease of varied etiology and ...

Machine Learning-Based Rapid Prediction of Torsional Performance of Personalized Peripheral Artery Stent.

International journal for numerical methods in biomedical engineering
The complex mechanical environment of peripheral arteries makes stents with poor torsional performance more prone to fracture, and stent fracture is considered a precursor to in-stent restenosis (ISR). Therefore, studying the torsional performance of...