AIMC Topic: Computed Tomography Angiography

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Artificial intelligence assistance improves the accuracy and efficiency of intracranial aneurysm detection with CT angiography.

European journal of radiology
PURPOSE: The aim of this study was to evaluate whether a novel head and neck artificial intelligence (AI)-assisted diagnostic system based on a three-dimensional convolutional neural network (3D-CNN) could improve the accuracy, efficiency and working...

Digital Subtraction Angiography Image Features under the Deep Learning Algorithm in Cardiovascular Interventional Treatment and Nursing for Vascular Restenosis.

Computational and mathematical methods in medicine
The objective of this study was to explore the application value of digital subtraction angiography (DSA) images optimized by deep learning algorithms in vascular restenosis patients undergoing cardiovascular intervention and their nursing efficacy. ...

Deep Learning to Automatically Segment and Analyze Abdominal Aortic Aneurysm from Computed Tomography Angiography.

Cardiovascular engineering and technology
PURPOSE: Although segmentation of Abdominal Aortic Aneurysms (AAA) thrombus is a crucial step for both the planning of endovascular treatment and the monitoring of the intervention's outcome, it is still performed manually implying time consuming ope...

Radiogenomics and Artificial Intelligence Approaches Applied to Cardiac Computed Tomography Angiography and Cardiac Magnetic Resonance for Precision Medicine in Coronary Heart Disease: A Systematic Review.

Circulation. Cardiovascular imaging
The risk of coronary heart disease (CHD) clinical manifestations and patient management is estimated according to risk scores accounting multifactorial risk factors, thus failing to cover the individual cardiovascular risk. Technological improvements...

CT Image Feature Diagnosis on the Basis of Deep Learning Algorithm for Preoperative Patients and Complications of Transcatheter Aortic Valve Implantation.

Journal of healthcare engineering
This work was aimed to explore the role of CT angiography information provided by deep learning algorithm in the diagnosis and complications of the disease focusing on congenital aortic valve disease and severe aortic valve stenosis. 120 patients who...

Calcium Scoring at Coronary CT Angiography Using Deep Learning.

Radiology
Background Separate noncontrast CT to quantify the coronary artery calcium (CAC) score often precedes coronary CT angiography (CTA). Quantifying CAC scores directly at CTA would eliminate the additional radiation produced at CT but remains challengin...

Radiation dose reduction with deep-learning image reconstruction for coronary computed tomography angiography.

European radiology
OBJECTIVES: Deep-learning image reconstruction (DLIR) offers unique opportunities for reducing image noise without degrading image quality or diagnostic accuracy in coronary CT angiography (CCTA). The present study aimed at exploiting the capabilitie...

Deep-learning image-reconstruction algorithm for dual-energy CT angiography with reduced iodine dose: preliminary results.

Clinical radiology
AIM: To evaluate the computed tomography (CT) attenuation values, background noise, arterial depiction, and image quality in whole-body dual-energy CT angiography (DECTA) at 40 keV with a reduced iodine dose using deep-learning image reconstruction (...

Automated Collateral Flow Assessment in Patients with Acute Ischemic Stroke Using Computed Tomography with Artificial Intelligence Algorithms.

World neurosurgery
BACKGROUND: Collateral circulation is associated with improved functional outcome in patients with large vessel occlusion acute ischemic stroke (AIS) who undergo reperfusion therapy. Assessment of collateral flow can be time consuming, subjective, an...