[HTML][HTML] A clinically applicable deep-learning model for detecting intracranial aneurysm in computed tomography angiography images
Z Shi, C Miao, UJ Schoepf, RH Savage… - Nature …, 2020 - nature.com
Intracranial aneurysm is a common life-threatening disease. Computed tomography
angiography is recommended as the standard diagnosis tool; yet, interpretation can be time …
angiography is recommended as the standard diagnosis tool; yet, interpretation can be time …
ARISE I Consensus Review on the Management of Intracranial Aneurysms
SI Tjoumakaris, R Hanel, J Mocco, M Ali-Aziz Sultan… - Stroke, 2024 - Am Heart Assoc
BACKGROUND: Intracranial aneurysms (IAs) remain a challenging neurological diagnosis
associated with significant morbidity and mortality. There is a plethora of microsurgical and …
associated with significant morbidity and mortality. There is a plethora of microsurgical and …
Metallic artifacts-free spectral computed tomography angiography based on renal clearable bismuth chelate
G Shu, L Zhao, F Li, Y Jiang, X Zhang, C Yu, J Pan… - Biomaterials, 2024 - Elsevier
Computed tomography angiography (CTA) is one of the most important diagnosis
techniques for various vascular diseases in clinic. However, metallic artifacts caused by …
techniques for various vascular diseases in clinic. However, metallic artifacts caused by …
Geometric deep learning using vascular surface meshes for modality-independent unruptured intracranial aneurysm detection
KM Timmins, IC Van der Schaaf, IN Vos… - IEEE transactions on …, 2023 - ieeexplore.ieee.org
Early detection of unruptured intracranial aneurysms (UIAs) enables better rupture risk and
preventative treatment assessment. UIAs are usually diagnosed on Time-of-Flight Magnetic …
preventative treatment assessment. UIAs are usually diagnosed on Time-of-Flight Magnetic …
Validation of an automated machine learning algorithm for the detection and analysis of cerebral aneurysms
M Colasurdo, D Shalev, A Robledo, V Vasandani… - Journal of …, 2023 - thejns.org
OBJECTIVE Machine learning algorithms have shown groundbreaking results in
neuroimaging. The authors herein evaluated the performance of a newly developed …
neuroimaging. The authors herein evaluated the performance of a newly developed …
[HTML][HTML] WRANet: wavelet integrated residual attention U-Net network for medical image segmentation
Medical image segmentation is crucial for the diagnosis and analysis of disease. Deep
convolutional neural network methods have achieved great success in medical image …
convolutional neural network methods have achieved great success in medical image …
A deep learning–based automatic system for intracranial aneurysms diagnosis on three‐dimensional digital subtraction angiographic images
Abstract Background Intracranial aneurysms (IAs) are a life‐threatening disease. Their
rupture can lead to hemorrhagic stroke. Most studies applying deep learning for the …
rupture can lead to hemorrhagic stroke. Most studies applying deep learning for the …
Automated unruptured cerebral aneurysms detection in TOF MR angiography images using dual-channel SE-3D UNet: a multi-center research
G Chen, B Yifang, Z Jiajun, W Dongdong, Z Zhiyong… - European …, 2023 - Springer
Objectives Time of flight magnetic resonance angiography (TOF-MRA) is the primary non-
invasive screening method for cerebral aneurysms. We aimed to develop a computer-aided …
invasive screening method for cerebral aneurysms. We aimed to develop a computer-aided …
[HTML][HTML] Dynamic evaluation of unruptured intracranial aneurysms by 4D-CT angiography: comparison with digital subtraction angiography (DSA) and surgical …
L Yang, X Gao, C Gao, S Xu, S Cao - BMC Medical Imaging, 2023 - Springer
Background This study was to prospectively investigate the feasibility of four-dimensional
computed tomography angiography (4D-CTA) with electrocardiogram-gated (ECG) …
computed tomography angiography (4D-CTA) with electrocardiogram-gated (ECG) …