AIMC Topic: Angiography, Digital Subtraction

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Performance of deep learning-based autodetection of arterial stenosis on head and neck CT angiography: an independent external validation study.

La Radiologia medica
PURPOSE: To externally validate the performance of automated stenosis detection on head and neck CT angiography (CTA) and investigate the impact factors using an independent bi-center dataset with digital subtraction angiography (DSA) as the ground t...

Multi-mode information fusion navigation system for robot-assisted vascular interventional surgery.

BMC surgery
BACKGROUND: Minimally invasive vascular intervention (MIVI) is a powerful technique for the treatment of cardiovascular diseases, such as abdominal aortic aneurysm (AAA), thoracic aortic aneurysm (TAA) and aortic dissection (AD). Navigation of tradit...

Deep Learning Subtraction Angiography: Improved Generalizability with Transfer Learning.

Journal of vascular and interventional radiology : JVIR
PURPOSE: To investigate the utility and generalizability of deep learning subtraction angiography (DLSA) for generating synthetic digital subtraction angiography (DSA) images without misalignment artifacts.

Application of deblur technology for improving the clarity of digital subtractive angiography.

Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences
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...

Automated Detection of Cerebral Aneurysms on TOF-MRA Using a Deep Learning Approach: An External Validation Study.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Cerebral aneurysms yield the risk of rupture, severe disability and death. Thus, early detection of cerebral aneurysms is crucial to ensure timely treatment, if necessary. AI-based software tools are expected to enhance radiol...

Deep Learning for Detection of Intracranial Aneurysms from Computed Tomography Angiography Images.

Journal of digital imaging
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...

Deep Learning-Based Digital Subtraction Angiography Characteristics in Nursing of Maintenance Hemodialysis Patients.

Contrast media & molecular imaging
This study is aimed at exploring the diagnostic value of digital subtraction angiography (DSA) based on faster region-based convolutional networks (Faster-RCNN) deep learning for maintenance hemodialysis (MHD) diseases and to provide a theoretical ba...

A deep learning-based automatic system for intracranial aneurysms diagnosis on three-dimensional digital subtraction angiographic images.

Medical physics
BACKGROUND: Intracranial aneurysms (IAs) are a life-threatening disease. Their rupture can lead to hemorrhagic stroke. Most studies applying deep learning for the detection of aneurysms are based on angiographic images. However, critical diagnostic i...

Deep Learning-Based Intraoperative Stent Graft Segmentation on Completion Digital Subtraction Angiography During Endovascular Aneurysm Repair.

Journal of endovascular therapy : an official journal of the International Society of Endovascular Specialists
PURPOSE: Modern endovascular hybrid operating rooms generate large amounts of medical images during a procedure, which are currently mostly assessed by eye. In this paper, we present fully automatic segmentation of the stent graft on the completion d...

Deep Learning-Based Magnetic Resonance Imaging in Diagnosis and Treatment of Intracranial Aneurysm.

Computational and mathematical methods in medicine
This study was focused on the positioning of the intracranial aneurysm in the magnetic resonance imaging (MRI) images using the deep learning-based U-Net model, to realize the computer-aided diagnosis of the intracranial aneurysm. First, a network wa...