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Endovascular Procedures

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A Deep Segmentation Network of Multi-Scale Feature Fusion Based on Attention Mechanism for IVOCT Lumen Contour.

IEEE/ACM transactions on computational biology and bioinformatics
Recently, coronary heart disease has attracted more and more attention, where segmentation and analysis for vascular lumen contour are helpful for treatment. And intravascular optical coherence tomography (IVOCT) images are used to display lumen shap...

Prediction of Clinical Outcome in Patients with Large-Vessel Acute Ischemic Stroke: Performance of Machine Learning versus SPAN-100.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Traditional statistical models and pretreatment scoring systems have been used to predict the outcome for acute ischemic stroke patients (AIS). Our aim was to select the most relevant features in terms of outcome prediction on...

Flow driven robotic navigation of microengineered endovascular probes.

Nature communications
Minimally invasive medical procedures, such as endovascular catheterization, have considerably reduced procedure time and associated complications. However, many regions inside the body, such as in the brain vasculature, still remain inaccessible due...

Predictive score for complete occlusion of intracranial aneurysms treated by flow-diverter stents using machine learning.

Journal of neurointerventional surgery
BACKGROUND: Complete occlusion of an intracranial aneurysm (IA) after the deployment of a flow-diverter stent is currently unpredictable. The aim of this study was to develop a predictive occlusion score based on pretreatment clinical and angiographi...

Machine learning for endoleak detection after endovascular aortic repair.

Scientific reports
Diagnosis of endoleak following endovascular aortic repair (EVAR) relies on manual review of multi-slice CT angiography (CTA) by physicians which is a tedious and time-consuming process that is susceptible to error. We evaluate the use of a deep neur...

Use of Natural Language Processing to Improve Identification of Patients With Peripheral Artery Disease.

Circulation. Cardiovascular interventions
BACKGROUND: Peripheral artery disease (PAD) is underrecognized, undertreated, and understudied: each of these endeavors requires efficient and accurate identification of patients with PAD. Currently, PAD patient identification relies on diagnosis/pro...

Tele-robotics and artificial-intelligence in stroke care.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
In the last forty years, the field of medicine has experienced dramatic shifts in technology-enhanced surgical procedures - from its initial use in 1985 for neurosurgical biopsies to current implementation of systems such as magnetic-guided catheters...

Data-efficient deep learning of radiological image data for outcome prediction after endovascular treatment of patients with acute ischemic stroke.

Computers in biology and medicine
Treatment selection is becoming increasingly more important in acute ischemic stroke patient care. Clinical variables and radiological image biomarkers (old age, pre-stroke mRS, NIHSS, occlusion location, ASPECTS, among others) have an important role...