AIMC Topic: Cerebral Arteries
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Accuracy of an nnUNet Neural Network for the Automatic Segmentation of Intracranial Aneurysms, Their Parent Vessels, and Major Cerebral Arteries from MRI-TOF.
AJNR. American journal of neuroradiology
May 2, 2025
BACKGROUND AND PURPOSE: The automatic recognition of intracraial aneurysms by means of machine-learning algorithms represents a new frontier for diagnostic and therapeutic goals. Yet, the current algorithms focus solely on the aneurysms and not on th...
Application and optimization of the U-Net++ model for cerebral artery segmentation based on computed tomographic angiography images.
European journal of radiology
Apr 27, 2025
Accurate segmentation of cerebral arteries on computed tomography angiography (CTA) images is essential for the diagnosis and management of cerebrovascular diseases, including ischemic stroke. This study implemented a deep learning-based U-Net++ mode...
Feasibility of U-Net model for cerebral arteries segmentation with low-dose computed tomography angiographic images with pre-processing methods.
Scientific reports
Apr 17, 2025
Subtraction computed tomography angiography (sCTA) can effectively separate enhanced cerebral arteries from similar signal intensity and proximity (i.e., vertebrae and skull). However, sCTA is not considered mainstream because of the high radiation d...
Reinforcement learning for safe autonomous two-device navigation of cerebral vessels in mechanical thrombectomy.
International journal of computer assisted radiology and surgery
Apr 3, 2025
PURPOSE: Autonomous systems in mechanical thrombectomy (MT) hold promise for reducing procedure times, minimizing radiation exposure, and enhancing patient safety. However, current reinforcement learning (RL) methods only reach the carotid arteries, ...
Improved visualization of intracranial distal arteries with multiple 2D slice dynamic ASL-MRA and super-resolution convolutional neural network.
Magnetic resonance in medicine
Aug 18, 2024
PURPOSE: To develop a novel framework to improve the visualization of distal arteries in arterial spin labeling (ASL) dynamic MRA.
Automated Cerebrovascular Segmentation and Visualization of Intracranial Time-of-Flight Magnetic Resonance Angiography Based on Deep Learning.
Journal of imaging informatics in medicine
Aug 12, 2024
Time-of-flight magnetic resonance angiography (TOF-MRA) is a non-contrast technique used to visualize neurovascular. However, manual reconstruction of the volume render (VR) by radiologists is time-consuming and labor-intensive. Deep learning-based (...
Accurate and robust segmentation of cerebral vasculature on four-dimensional arterial spin labeling magnetic resonance angiography using machine-learning approach.
Magnetic resonance imaging
Apr 16, 2024
Segmentation of cerebral vasculature on MR vascular images is of great significance for clinical application and research. However, the existing cerebrovascular segmentation approaches are limited due to insufficient image contrast and complicated al...
Automated in-depth cerebral arterial labelling using cerebrovascular vasculature reframing and deep neural networks.
Scientific reports
Feb 24, 2023
Identifying the cerebral arterial branches is essential for undertaking a computational approach to cerebrovascular imaging. However, the complexity and inter-individual differences involved in this process have not been thoroughly studied. We used m...
Automated segmentation of multiparametric magnetic resonance images for cerebral AVM radiosurgery planning: a deep learning approach.
Scientific reports
Jan 17, 2022
Stereotactic radiosurgery planning for cerebral arteriovenous malformations (AVM) is complicated by the variability in appearance of an AVM nidus across different imaging modalities. We developed a deep learning approach to automatically segment cere...
Statistical modeling and knowledge-based segmentation of cerebral artery based on TOF-MRA and MR-T1.
Computer methods and programs in biomedicine
Nov 14, 2019
BACKGROUND AND OBJECTIVE: For cerebrovascular segmentation from time-of-flight (TOF) magnetic resonance angiography (MRA), the focused issues are segmentation accuracy, vascular network coverage ratio, and cerebral artery and vein (CA/CV) separation....
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