AIMC Topic: Arteries
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A machine learning based algorithm accurately stages liver disease by quantification of arteries.
Scientific reports
Jan 24, 2025
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 ...
Physics-Informed Graph Neural Networks to solve 1-D equations of blood flow.
Computer methods and programs in biomedicine
Sep 20, 2024
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...
Thrombosed Persistent Median Artery with Coexisting Bifid Median Nerve in a Robotic Arthroplasty Surgeon: A Case Report.
JBJS case connector
Apr 18, 2024
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...
Examining arterial pulsation to identify and risk-stratify heart failure subjects with deep neural network.
Physical and engineering sciences in medicine
Feb 15, 2024
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...
Sensitivity analysis of the mechanical properties on atherosclerotic arteries rupture risk with an artificial neural network method.
Computer methods in biomechanics and biomedical engineering
Jan 25, 2024
Considering the differences between individuals, in this paper, an uncertainty analysis model for predicting rupture risk of atherosclerotic arteries is established based on a back-propagation artificial neural network. The influence of isotropy and ...
Transformer-based deep learning denoising of single and multi-delay 3D arterial spin labeling.
Magnetic resonance in medicine
Oct 17, 2023
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 ...
Non-invasive arterial blood pressure measurement and SpO estimation using PPG signal: a deep learning framework.
BMC medical informatics and decision making
Jul 21, 2023
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...
Deep learning for artery-vein classification in optical coherence tomography angiography.
Experimental biology and medicine (Maywood, N.J.)
Jul 15, 2023
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 ...
A hybrid approach to full-scale reconstruction of renal arterial network.
Scientific reports
May 9, 2023
The renal vasculature, acting as a resource distribution network, plays an important role in both the physiology and pathophysiology of the kidney. However, no imaging techniques allow an assessment of the structure and function of the renal vasculat...
Editorial for "Deep Learning-Based Acceleration of Compressed Sensing Noncontrast-Enhanced Coronary Magnetic Resonance Angiography in Patients With Suspected Coronary Artery Disease".
Journal of magnetic resonance imaging : JMRI
Feb 21, 2023
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