Artificial intelligence in the management of intracranial aneurysms: current status and future perspectives

Z Shi, B Hu, UJ Schoepf, RH Savage… - American Journal …, 2020 - Am Soc 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 …

Artificial intelligence applications in intracranial aneurysm: achievements, challenges and opportunities

O Alwalid, X Long, M Xie, P Han - Academic Radiology, 2022 - Elsevier
Intracranial aneurysms present in about 3% of the general population and the number of
detected aneurysms is continuously rising with the advances in imaging techniques …

Deep learning-based recognition and segmentation of intracranial aneurysms under small sample size

G Zhu, X Luo, T Yang, L Cai, JH Yeo, G Yan… - Frontiers in …, 2022 - frontiersin.org
The manual identification and segmentation of intracranial aneurysms (IAs) involved in the
3D reconstruction procedure are labor-intensive and prone to human errors. To meet the …

Assessing accuracy and consistency in intracranial aneurysm sizing: human expertise vs. artificial intelligence

A Planinc, N Špegel, Z Podobnik, U Šinigoj, P Skubic… - Scientific reports, 2024 - nature.com
Intracranial aneurysms (IAs) are a common vascular pathology and are associated with a
risk of rupture, which is often fatal. Aneurysm growth of more than 1 mm is considered a …

Integrated Deep Learning Model for the Detection, Segmentation, and Morphologic Analysis of Intracranial Aneurysms Using CT Angiography

Y Yang, Z Chang, X Nie, J Wu, J Chen, W Liu… - Radiology: Artificial …, 2024 - pubs.rsna.org
“Just Accepted” papers have undergone full peer review and have been accepted for
publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout …

Volumetric surveillance of brain aneurysms: pitfalls of MRA

A Raghuram, R Patel, A Varon… - Interventional …, 2023 - journals.sagepub.com
Introduction Untreated brain aneurysms are usually surveilled with serial MR imaging and
evaluated with 2D multiplanar measurements. The assessment of aneurysm growth may be …

[HTML][HTML] Patient-specific computational modelling of endovascular treatment for intracranial aneurysms

B Bisighini, M Aguirre, B Pierrat, S Avril - Brain Multiphysics, 2023 - Elsevier
Endovascular techniques, such as endoluminal or endosaccular reconstruction, have
emerged as the preferred method for treating both ruptured and unruptured intracranial …

Imaging of Intracranial Aneurysms: A Review of Standard and Advanced Imaging Techniques

SS Veeturi, S Hall, S Fujimura, M Mossa-Basha… - Translational Stroke …, 2024 - Springer
The treatment of intracranial aneurysms is dictated by its risk of rupture in the future. Several
clinical and radiological risk factors for aneurysm rupture have been described and …

Accuracy and reliability of computer-assisted semi-automated morphological analysis of intracranial aneurysms: an experimental study with digital phantoms and …

J Geng, P Hu, Z Ji, C Li, L Li, J Shen, X Feng… - International Journal of …, 2020 - Springer
Purpose Morphological parameters are very important for predicting aneurysm rupture.
However, due to geometric radiographic distortion and plane/angle selection bias, the …

Application of convolutional network models in detection of intracranial aneurysms: a systematic review and meta-analysis

S Abdollahifard, A Farrokhi, F Kheshti… - Interventional …, 2023 - journals.sagepub.com
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 …