AIMC Topic: Angiography, Digital Subtraction

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Evaluation of an Artificial Intelligence-Based 3D-Angiography for Visualization of Cerebral Vasculature.

Clinical neuroradiology
PURPOSE: The three-dimensional digital subtraction angiography (3D DSA) technique is the current standard and is based on both mask and fill runs to enable the subtraction technique. Artificial intelligence (AI)-based 3D angiography (3DA) was develop...

Automatic radiomic feature extraction using deep learning for angiographic parametric imaging of intracranial aneurysms.

Journal of neurointerventional surgery
BACKGROUND: Angiographic parametric imaging (API) is an imaging method that uses digital subtraction angiography (DSA) to characterize contrast media dynamics throughout the vasculature. This requires manual placement of a region of interest over a l...

Deep learning-based digital subtraction angiography image generation.

International journal of computer assisted radiology and surgery
PURPOSE: Digital subtraction angiography (DSA) is a powerful technique for diagnosing cardiovascular disease. In order to avoid image artifacts caused by patient movement during imaging, we take deep learning-based methods to generate DSA image from ...

Multitask Deep Learning for Automated Detection of Endoleak at Digital Subtraction Angiography during Endovascular Aneurysm Repair.

Radiology. Artificial intelligence
Purpose To develop and evaluate a novel multitask deep learning framework for automated detection and localization of endoleaks at aortic digital subtraction angiography (DSA) performed during real-world endovascular aneurysm repair (EVAR) procedures...

Advancing Intracranial Aneurysm Detection: A Comprehensive Systematic Review and Meta-analysis of Deep Learning Models Performance, Clinical Integration, and Future Directions.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
BACKGROUND: Cerebral aneurysms pose a significant risk to patient safety, particularly when ruptured, emphasizing the need for early detection and accurate prediction. Traditional diagnostic methods, reliant on clinician-based evaluations, face chall...

Development and Validation of a Sham-AI Model for Intracranial Aneurysm Detection at CT Angiography.

Radiology. Artificial intelligence
Purpose To evaluate a sham-artificial intelligence (AI) model acting as a placebo control for a standard-AI model for diagnosis of intracranial aneurysm. Materials and Methods This retrospective crossover, blinded, multireader, multicase study was co...

Knowledge-Augmented Deep Learning for Segmenting and Detecting Cerebral Aneurysms With CT Angiography: A Multicenter Study.

Radiology
Background Deep learning (DL) could improve the labor-intensive, challenging processes of diagnosing cerebral aneurysms but requires large multicenter data sets. Purpose To construct a DL model using a multicenter data set for accurate cerebral aneur...

Evaluating a 3D deep learning pipeline for cerebral vessel and intracranial aneurysm segmentation from computed tomography angiography-digital subtraction angiography image pairs.

Neurosurgical focus
OBJECTIVE: Computed tomography angiography (CTA) is the most widely used imaging modality for intracranial aneurysm (IA) management, yet it remains inferior to digital subtraction angiography (DSA) for IA detection, particularly of small IAs in the c...

[Development of the DSA Method for Coronary Angiography Using Deep Learning Techniques].

Nihon Hoshasen Gijutsu Gakkai zasshi
PURPOSE: DSA processing is not applied to the coronary artery because heavy artifacts will be generated in DSA images by heart beats and breathing of the patient. However, DSA images of coronary artery contribute to the accuracy of diagnosis and eluc...

[Perioperative stroke effectively treated by an acute stroke team including anesthesia department: a case report].

Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences
Perioperative stroke is cerebral infarction occurring in the perioperative period. The incidence of perioperative stroke in non-cardiac, and non-neurologic surgery is about 0.7%, but the mortality can be as high as 26% to 40%. The outcome of the pati...