AIMC Topic: Cerebral Angiography
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Deep learning for collateral evaluation in ischemic stroke with imbalanced data.
International journal of computer assisted radiology and surgery
Jan 12, 2023
PURPOSE: Collateral evaluation is typically done using visual inspection of cerebral images and thus suffers from intra- and inter-rater variability. Large open databases of ischemic stroke patients are rare, limiting the use of deep learning methods...
Deep learning-based semantic vessel graph extraction for intracranial aneurysm rupture risk management.
International journal of computer assisted radiology and surgery
Jan 10, 2023
PURPOSE: Intracranial aneurysms are vascular deformations in the brain which are complicated to treat. In clinical routines, the risk assessment of intracranial aneurysm rupture is simplified and might be unreliable, especially for patients with mult...
Application of deblur technology for improving the clarity of digital subtractive angiography.
Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences
Dec 1, 2022
BACKGROUND: Digital subtraction angiography (DSA) is most commonly used in vessel disease examinations and treatments. We aimed to develop a novel deep learning-based method to deblur the large focal spot DSA images, so as to obtain a clearer and sha...
Deep Learning for Detection of Intracranial Aneurysms from Computed Tomography Angiography Images.
Journal of digital imaging
Sep 9, 2022
The accuracy of computed tomography angiography (CTA) image interpretation depends on the radiologist. This study aims to develop a new method for automatically detecting intracranial aneurysms from CTA images using deep learning, based on a convolut...
DSA Image Analysis of Clinical Features and Nursing Care of Cerebral Aneurysm Patients Based on the Deep Learning Algorithm.
Scanning
Aug 13, 2022
OBJECTIVE: A deep learning algorithm was developed for automatic detection and localization of intracranial aneurysms in DSA, and its clinical characteristics were analyzed, and targeted nursing measures were formulated.
Value of 4D CT Angiography Combined with Whole Brain CT Perfusion Imaging Feature Analysis under Deep Learning in Imaging Examination of Acute Ischemic Stroke.
Computational intelligence and neuroscience
Jun 13, 2022
This study was aimed at investigating the application of deep learning 4D computed tomography angiography (CTA) combined with whole brain CT perfusion (CTP) imaging in acute ischemic stroke (AIS). A total of 46 patients with ischemic stroke were sele...
Early Diagnosis of Acute Ischemic Stroke by Brain Computed Tomography Perfusion Imaging Combined with Head and Neck Computed Tomography Angiography on Deep Learning Algorithm.
Contrast media & molecular imaging
May 9, 2022
The purpose of the research was to discuss the application values of deep learning algorithm-based computed tomography perfusion (CTP) imaging combined with head and neck computed tomography angiography (CTA) in the diagnosis of ultra-early acute isc...
Artificial intelligence assistance improves the accuracy and efficiency of intracranial aneurysm detection with CT angiography.
European journal of radiology
Jan 20, 2022
PURPOSE: The aim of this study was to evaluate whether a novel head and neck artificial intelligence (AI)-assisted diagnostic system based on a three-dimensional convolutional neural network (3D-CNN) could improve the accuracy, efficiency and working...
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...
Robotics in neurointerventional surgery: a systematic review of the literature.
Journal of neurointerventional surgery
Nov 19, 2021
BACKGROUND: Robotically performed neurointerventional surgery has the potential to reduce occupational hazards to staff, perform intervention with greater precision, and could be a viable solution for teleoperated neurointerventional procedures.
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