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Intracranial Aneurysm

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Deep Learning-Based Software Improves Clinicians' Detection Sensitivity of Aneurysms on Brain TOF-MRA.

AJNR. American journal of neuroradiology Aug 12, 2021
BACKGROUND AND PURPOSE: The detection of cerebral aneurysms on MRA is a challenging task. Recent studies have used deep learning-based software for automated detection of aneurysms on MRA and have reported high performance. The purpose of this study ...
Humans Sensitivity and Specificity Deep Learning Magnetic Resonance Angiography Intracranial Aneurysm Software Brain Retrospective Studies
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Three Fundamental Elements for Deep Learning-based Computer-assisted Diagnostic Tools of Intracranial Aneurysms.

Radiology May 18, 2021
Deep Learning Magnetic Resonance Angiography Intracranial Aneurysm Humans Computers Retrospective Studies
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Deep learning assistance increases the detection sensitivity of radiologists for secondary intracranial aneurysms in subarachnoid hemorrhage.

Neuroradiology Apr 10, 2021
PURPOSE: To evaluate whether a deep learning model (DLM) could increase the detection sensitivity of radiologists for intracranial aneurysms on CT angiography (CTA) in aneurysmal subarachnoid hemorrhage (aSAH).
Sensitivity and Specificity Humans Deep Learning Radiologists Subarachnoid Hemorrhage Cerebral Angiography Angiography, Digital Subtraction Intracranial Aneurysm
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Machine Learning-Based Prediction of Small Intracranial Aneurysm Rupture Status Using CTA-Derived Hemodynamics: A Multicenter Study.

AJNR. American journal of neuroradiology Mar 4, 2021
BACKGROUND AND PURPOSE: Small intracranial aneurysms are being increasingly detected while the rupture risk is not well-understood. We aimed to develop rupture-risk models of small aneurysms by combining clinical, morphologic, and hemodynamic informa...
Humans Aneurysm, Ruptured Intracranial Aneurysm Machine Learning Retrospective Studies Hemodynamics
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Fully automated detection and segmentation of intracranial aneurysms in subarachnoid hemorrhage on CTA using deep learning.

Scientific reports Dec 11, 2020
In aneurysmal subarachnoid hemorrhage (aSAH), accurate diagnosis of aneurysm is essential for subsequent treatment to prevent rebleeding. However, aneurysm detection proves to be challenging and time-consuming. The purpose of this study was to develo...
Aged Adult Male Humans Female Computed Tomography Angiography Cerebral Angiography Intracranial Aneurysm Middle Aged Deep Learning Subarachnoid Hemorrhage
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A clinically applicable deep-learning model for detecting intracranial aneurysm in computed tomography angiography images.

Nature communications Nov 30, 2020
Intracranial aneurysm is a common life-threatening disease. Computed tomography angiography is recommended as the standard diagnosis tool; yet, interpretation can be time-consuming and challenging. We present a specific deep-learning-based model trai...
Algorithms Angiography, Digital Subtraction Prospective Studies Computed Tomography Angiography Imaging, Three-Dimensional Tomography, X-Ray Computed Intracranial Aneurysm Stroke Brain Ischemia Male Humans Middle Aged Deep Learning Female China Aged Sensitivity and Specificity
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Predictive score for complete occlusion of intracranial aneurysms treated by flow-diverter stents using machine learning.

Journal of neurointerventional surgery Nov 20, 2020
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...
Humans Machine Learning Algorithms Female Adult Prospective Studies Retrospective Studies Endovascular Procedures Self Expandable Metallic Stents Intracranial Aneurysm Balloon Occlusion Treatment Outcome Male Follow-Up Studies Middle Aged Predictive Value of Tests Cohort Studies
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Automated Aneurysm Detection: Emerging from the Shallow End of the Deep Learning Pool.

Radiology Nov 3, 2020
Deep Learning Computed Tomography Angiography Intracranial Aneurysm Machine Learning Algorithms Humans
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Deep Learning for Detecting Cerebral Aneurysms with CT Angiography.

Radiology Nov 3, 2020
Background Cerebral aneurysm detection is a challenging task. Deep learning may become a supportive tool for more accurate interpretation. Purpose To develop a highly sensitive deep learning-based algorithm that assists in the detection of cerebral a...
Intracranial Aneurysm Reproducibility of Results Sensitivity and Specificity Male Image Interpretation, Computer-Assisted Computed Tomography Angiography Middle Aged Deep Learning Humans Retrospective Studies Female
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Radiomic Model for Distinguishing Dissecting Aneurysms from Complicated Saccular Aneurysms on high-Resolution Magnetic Resonance Imaging.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association Sep 8, 2020
OBJECTIVE: To build radiomic model in differentiating dissecting aneurysm (DA) from complicated saccular aneurysm (SA) based on high-resolution magnetic resonance imaging (HR-MRI) through machine-learning algorithm.
Aortic Dissection Intracranial Aneurysm Adult Female Humans Male Predictive Value of Tests Magnetic Resonance Imaging Reproducibility of Results Middle Aged Machine Learning Image Interpretation, Computer-Assisted Diagnosis, Differential Aged Retrospective Studies
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