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 …

Background Subarachnoid hemorrhage from cerebral aneurysm rupture is a major cause of
morbidity and mortality. Early aneurysm identification, aided by automated systems, may …

Intracranial aneurysms are a common asymptomatic vascular pathology, the rupture of
which is a devastating event with a significant risk of morbidity and mortality. Aneurysm …

Intracranial aneurysm is commonly found in human brains especially for the elderly, and its
rupture accounts for a high rate of subarachnoid hemorrhages. However, it is time …

Purpose Cerebrovascular aneurysms are being observed with rapidly increasing incidence.
Therefore, tools are needed for accurate and efficient detection of aneurysms. We used …

It is possible to identify unruptured intracranial aneurysms (UIA) using machine learning
(ML) algorithms, which can be a life-saving strategy, especially in high-risk populations. To …

Objectives To develop a deep learning algorithm for automated detection and localization of
intracranial aneurysms on time-of-flight MR angiography and evaluate its diagnostic …

The assessment of rupture probability is crucial to identifying at risk intracranial aneurysms
(IA) in patients harboring multiple aneurysms. We aimed to develop a computer-assisted …

BACKGROUND AND PURPOSE: The rupture of an intracranial aneurysm is a serious
incident, causing subarachnoid hemorrhage associated with high fatality and morbidity …

In aneurysmal subarachnoid hemorrhage (aSAH), accurate diagnosis of aneurysm is
essential for subsequent treatment to prevent rebleeding. However, aneurysm detection …