AIMC Topic: Intracranial Aneurysm

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Development of machine learning-based preoperative predictive analytics for unruptured intracranial aneurysm surgery: a pilot study.

Acta neurochirurgica
BACKGROUND: The decision to treat unruptured intracranial aneurysms (UIAs) or not is complex and requires balancing of risk factors and scores. Machine learning (ML) algorithms have previously been effective at generating highly accurate and comprehe...

Prediction of Intracranial Aneurysm Risk using Machine Learning.

Scientific reports
An efficient method for identifying subjects at high risk of an intracranial aneurysm (IA) is warranted to provide adequate radiological screening guidelines and effectively allocate medical resources. We developed a model for pre-diagnosis IA predic...

Artificial Intelligence in the Management of Intracranial Aneurysms: Current Status and Future Perspectives.

AJNR. American journal of neuroradiology
Intracranial aneurysms with subarachnoid hemorrhage lead to high morbidity and mortality. It is of critical importance to detect aneurysms, identify risk factors of rupture, and predict treatment response of aneurysms to guide clinical interventions....

Deep learning for automated cerebral aneurysm detection on computed tomography images.

International journal of computer assisted radiology and surgery
PURPOSE: Cerebrovascular aneurysms are being observed with rapidly increasing incidence. Therefore, tools are needed for accurate and efficient detection of aneurysms. We used deep learning techniques with CT angiography acquired from multiple medica...

Feasibility study for use of angiographic parametric imaging and deep neural networks for intracranial aneurysm occlusion prediction.

Journal of neurointerventional surgery
BACKGROUND: Angiographic parametric imaging (API), based on digital subtraction angiography (DSA), is a quantitative imaging tool that may be used to extract contrast flow parameters related to hemodynamic conditions in abnormal pathologies such as i...

Automatic detection on intracranial aneurysm from digital subtraction angiography with cascade convolutional neural networks.

Biomedical engineering online
BACKGROUND: An intracranial aneurysm is a cerebrovascular disorder that can result in various diseases. Clinically, diagnosis of an intracranial aneurysm utilizes digital subtraction angiography (DSA) modality as gold standard. The existing automatic...

Evaluation of an Artificial Intelligence-Based 3D-Angiography for Visualization of Cerebral Vasculature.

Clinical neuroradiology
PURPOSE: The three-dimensional digital subtraction angiography (3D DSA) technique is the current standard and is based on both mask and fill runs to enable the subtraction technique. Artificial intelligence (AI)-based 3D angiography (3DA) was develop...

Comparison of statistical learning approaches for cerebral aneurysm rupture assessment.

International journal of computer assisted radiology and surgery
PURPOSE: Incidental aneurysms pose a challenge to physicians who need to decide whether or not to treat them. A statistical model could potentially support such treatment decisions. The aim of this study was to compare a previously developed aneurysm...

Automatic radiomic feature extraction using deep learning for angiographic parametric imaging of intracranial aneurysms.

Journal of neurointerventional surgery
BACKGROUND: Angiographic parametric imaging (API) is an imaging method that uses digital subtraction angiography (DSA) to characterize contrast media dynamics throughout the vasculature. This requires manual placement of a region of interest over a l...