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Computed Tomography Angiography

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[Coronary artery segmentation based on Transformer and convolutional neural networks dual parallel branch encoder neural network].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Manual segmentation of coronary arteries in computed tomography angiography (CTA) images is inefficient, and existing deep learning segmentation models often exhibit low accuracy on coronary artery images. Inspired by the Transformer architecture, th...

Deep learning based automatic quantification of aortic valve calcification on contrast enhanced coronary CT angiography.

Scientific reports
Quantifying aortic valve calcification is critical for assessing the severity of aortic stenosis, predicting cardiovascular risk, and guiding treatment decisions. This study evaluated the feasibility of a deep learning-based automatic quantification ...

Artificial intelligence driven plaque characterization and functional assessment from CCTA using OCT-based automation: A prospective study.

International journal of cardiology
BACKGROUND: We aimed to develop and validate an Artificial Intelligence (AI) model that leverages CCTA and optical coherence tomography (OCT) images for automated analysis of plaque characteristics and coronary function.

Forecasting trends of rising emergency department chest imaging using machine learning.

Emergency radiology
INTRODUCTION: Imaging studies in the acute care setting, such as the emergency room, have been increasing. In this report, we use the Centers for Medicare and Medicaid services (CMS) database to assess trends in ED chest CT and chest CTA imaging in E...

Deep learning-driven pulmonary artery and vein segmentation reveals demography-associated vasculature anatomical differences.

Nature communications
Pulmonary artery-vein segmentation is critical for disease diagnosis and surgical planning. Traditional methods rely on Computed Tomography Pulmonary Angiography (CTPA), which requires contrast agents with potential health risks. Non-contrast CT, a s...

A dual-branch hybrid network with bilateral-difference awareness for collateral scoring on CT angiography of acute ischemic stroke patients.

Physics in medicine and biology
Acute ischemic stroke (AIS) patients with good collaterals tend to have better outcomes after endovascular therapy. Existing collateral scoring methods rely mainly on vessel segmentation and convolutional neural networks (CNNs), often ignoring bilate...

AI-based detection and classification of anomalous aortic origin of coronary arteries using coronary CT angiography images.

Nature communications
Anomalous aortic origin of the coronary artery (AAOCA) is a rare cardiac condition that can lead to ischemia or sudden cardiac death, yet it is often overlooked or falsely classified in routine coronary CT angiography (CCTA). Here, we developed, vali...

Unsupervised Domain Adaptation for Cross-Modality Cerebrovascular Segmentation.

IEEE journal of biomedical and health informatics
Cerebrovascular segmentation from time-of-flight magnetic resonance angiography (TOF-MRA) and computed tomography angiography (CTA) is essential in providing supportive information for diagnosing and treatment planning of multiple intracranial vascul...