AIMC Topic: Computed Tomography Angiography

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A computed tomography angiography-based radiomics model for prognostic prediction of endovascular abdominal aortic repair.

International journal of cardiology
OBJECTIVE: This study aims to develop a radiomics machine learning (ML) model that uses preoperative computed tomography angiography (CTA) data to predict the prognosis of endovascular aneurysm repair (EVAR) for abdominal aortic aneurysm (AAA) patien...

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...

Deep Learning-Based ASPECTS Algorithm Enhances Reader Performance and Reduces Interpretation Time.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: ASPECTS is a long-standing and well-documented selection criterion for acute ischemic stroke treatment; however, the interpretation of ASPECTS is a challenging and time-consuming task for physicians with notable interobserver ...

Automated Coronary Artery Segmentation with 3D PSPNET using Global Processing and Patch Based Methods on CCTA Images.

Cardiovascular engineering and technology
The prevalence of coronary artery disease (CAD) has become the major cause of death across the world in recent years. The accurate segmentation of coronary artery is important in clinical diagnosis and treatment of coronary artery disease (CAD) such ...