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

The use of artificial intelligence (AI) and robotics in endovascular neurosurgery promises to
transform neurovascular care. We present a review of the recently published neurosurgical …

Abstract Background Intracranial aneurysms (IAs) are a life‐threatening disease. Their
rupture can lead to hemorrhagic stroke. Most studies applying deep learning for the …

Brain aneurysm detection in Time-Of-Flight Magnetic Resonance Angiography (TOF-MRA)
has undergone drastic improvements with the advent of Deep Learning (DL). However …

Simple Summary Many of the rules considered valid in the ambit of lameness detection in
domestic animals are mainly subjective or acquired after extended clinical experience. Thus …

Introduction Intracranial aneurysms have a high prevalence in human population. It also has
a heavy burden of disease and high mortality rate in the case of rupture. Convolutional …

Background The morphological assessment of cerebral aneurysms based on cerebral
angiography is an essential step when planning strategy and device selection in …

MR imaging, a noninvasive radiation-free imaging modality commonly used during clinical
follow-up, has been widely utilized to reconstruct realistic 3D vascular models for patient …

The detection and segmentation of cerebral aneurysms is a crucial step in the development
of a clinical decision support system for estimating aneurysm rupture risk. However …

近年来, 人工智能在计算机科学领域快速崛起. 医学成像过程中产生了海量图像信息,
因此非常适合采用人工智能技术进行相关数据处理. 脑卒中患者神经影像在临床诊断 …