Deep learning–based detection of intracranial aneurysms in 3D TOF-MRA
BACKGROUND AND PURPOSE: The rupture of an intracranial aneurysm is a serious
incident, causing subarachnoid hemorrhage associated with high fatality and morbidity …
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
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 …
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 …
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 …
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
Purpose Cerebrovascular aneurysms are being observed with rapidly increasing incidence.
Therefore, tools are needed for accurate and efficient detection of aneurysms. We used …
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
Background The usefulness of computer‐assisted detection (CAD) for detecting cerebral
aneurysms has been reported; therefore, the improved performance of CAD will help to …
aneurysms has been reported; therefore, the improved performance of CAD will help to …
Deep learning for detecting cerebral aneurysms with CT angiography
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 …
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 …
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 …
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 …
important for rupture risk assessment and to allow an informed treatment decision to be …
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