Deep learning–based detection of intracranial aneurysms in 3D TOF-MRA

T Sichtermann, A Faron, R Sijben… - American Journal …, 2019 - Am Soc Neuroradiology
BACKGROUND AND PURPOSE: The rupture of an intracranial aneurysm is a serious
incident, causing subarachnoid hemorrhage associated with high fatality and morbidity …

Performance of a deep-learning neural network to detect intracranial aneurysms from 3D TOF-MRA compared to human readers

A Faron, T Sichtermann, N Teichert, JA Luetkens… - Clinical …, 2020 - Springer
Purpose To study the clinical potential of a deep learning neural network (convolutional
neural networks [CNN]) as a supportive tool for detection of intracranial aneurysms from 3D …

A deep learning algorithm may automate intracranial aneurysm detection on MR angiography with high diagnostic performance

B Joo, SS Ahn, PH Yoon, S Bae, B Sohn, YE Lee… - European …, 2020 - Springer
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 …

Deep learning for MR angiography: automated detection of cerebral aneurysms

D Ueda, A Yamamoto, M Nishimori, T Shimono… - Radiology, 2019 - pubs.rsna.org
Purpose To develop and evaluate a supportive algorithm using deep learning for detecting
cerebral aneurysms at time-of-flight MR angiography to provide a second assessment of …

Deep learning for automated cerebral aneurysm detection on computed tomography images

X Dai, L Huang, Y Qian, S Xia, W Chong, J Liu… - International Journal of …, 2020 - Springer
Purpose Cerebrovascular aneurysms are being observed with rapidly increasing incidence.
Therefore, tools are needed for accurate and efficient detection of aneurysms. We used …

Deep neural network‐based computer‐assisted detection of cerebral aneurysms in MR angiography

T Nakao, S Hanaoka, Y Nomura, I Sato… - Journal of Magnetic …, 2018 - Wiley Online Library
Background The usefulness of computer‐assisted detection (CAD) for detecting cerebral
aneurysms has been reported; therefore, the improved performance of CAD will help to …

Deep learning for detecting cerebral aneurysms with CT angiography

J Yang, M Xie, C Hu, O Alwalid, Y Xu, J Liu, T Jin, C Li… - Radiology, 2021 - pubs.rsna.org
Background Cerebral aneurysm detection is a challenging task. Deep learning may become
a supportive tool for more accurate interpretation. Purpose To develop a highly sensitive …

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 …

Accurate diagnosis of small cerebral aneurysms≤ 5 mm in diameter with 3.0-T MR angiography

MH Li, YD Li, BX Gu, YS Cheng, W Wang, HQ Tan… - Radiology, 2014 - pubs.rsna.org
Purpose To evaluate the diagnostic accuracy of three-dimensional (3D) time-of-flight (TOF)
magnetic resonance (MR) angiography at 3.0 T in the detection of small cerebral …

[HTML][HTML] Comparing methods of detecting and segmenting unruptured intracranial aneurysms on TOF-MRAS: the ADAM challenge

KM Timmins, IC van der Schaaf, E Bennink… - Neuroimage, 2021 - Elsevier
Accurate detection and quantification of unruptured intracranial aneurysms (UIAs) is
important for rupture risk assessment and to allow an informed treatment decision to be …