AIMC Topic: Angiography, Digital Subtraction

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Deep learning assistance increases the detection sensitivity of radiologists for secondary intracranial aneurysms in subarachnoid hemorrhage.

Neuroradiology
PURPOSE: To evaluate whether a deep learning model (DLM) could increase the detection sensitivity of radiologists for intracranial aneurysms on CT angiography (CTA) in aneurysmal subarachnoid hemorrhage (aSAH).

Deep Learning-based Angiogram Generation Model for Cerebral Angiography without Misregistration Artifacts.

Radiology
Background Digital subtraction angiography (DSA) generates an image by subtracting a mask image from a dynamic angiogram. However, patient movement-caused misregistration artifacts can result in unclear DSA images that interrupt procedures. Purpose T...

Deep learning-based classification of lower extremity arterial stenosis in computed tomography angiography.

European journal of radiology
PURPOSE: The purpose of this study is to develop and evaluate a deep learning model to assist radiologists in classifying lower extremity arteries based on the degree of arterial stenosis caused by plaque in lower extremity computed tomography angiog...

A clinically applicable deep-learning model for detecting intracranial aneurysm in computed tomography angiography images.

Nature communications
Intracranial aneurysm is a common life-threatening disease. Computed tomography angiography is recommended as the standard diagnosis tool; yet, interpretation can be time-consuming and challenging. We present a specific deep-learning-based model trai...

Deep learning based detection of intracranial aneurysms on digital subtraction angiography: A feasibility study.

The neuroradiology journal
BACKGROUND: Digital subtraction angiography is the gold standard for detecting and characterising aneurysms. Here, we assess the feasibility of commercial-grade deep learning software for the detection of intracranial aneurysms on whole-brain anterop...

Feasibility study for use of angiographic parametric imaging and deep neural networks for intracranial aneurysm occlusion prediction.

Journal of neurointerventional surgery
BACKGROUND: Angiographic parametric imaging (API), based on digital subtraction angiography (DSA), is a quantitative imaging tool that may be used to extract contrast flow parameters related to hemodynamic conditions in abnormal pathologies such as i...

Automatic detection on intracranial aneurysm from digital subtraction angiography with cascade convolutional neural networks.

Biomedical engineering online
BACKGROUND: An intracranial aneurysm is a cerebrovascular disorder that can result in various diseases. Clinically, diagnosis of an intracranial aneurysm utilizes digital subtraction angiography (DSA) modality as gold standard. The existing automatic...

A neural network approach to segment brain blood vessels in digital subtraction angiography.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Cerebrovascular diseases (CVDs) affect a large number of patients and often have devastating outcomes. The hallmarks of CVDs are the abnormalities formed on brain blood vessels, including protrusions, narrows, widening, and ...